Research ArticleCollaborative Knowledge Framework for Mediation InformationSystem Engineering

Wenxin Mu1 Frederick Benaben2 Nicolas Boissel-Dallier3 and Herve Pingaud4

1School of Economics and Management Beijing Jiaotong University Shangyuancun 3 Xizhimenwai Haidian Beijing 100044 China2Toulouse University Mines DrsquoAlbi Campus Jarlard Route de Teillet 81013 Albi France3InteropSys 23 Bd Victor Hugo 31770 Colomiers France4Champollion University Place Verdun 81012 Albi France

Correspondence should be addressed to Wenxin Mu wxmubjtueducn

Received 3 March 2017 Revised 7 May 2017 Accepted 30 August 2017 Published 23 October 2017

Academic Editor Kwok-Yan Lam

Copyright copy 2017 Wenxin Mu et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

With the worldwide interenterprise collaboration and interoperability background automatic collaborative business processdeduction is crucial and imperative researching subject Amethodology of deducing collaborative process is designed by collectingcollaborative knowledge Due to the complexity of deduction methodology a collaborative knowledge framework is defined toorganize abstract and concrete collaborative information The collaborative knowledge framework contains three dimensionselements levels and life cycle To better define the framework the relations in each dimension are explained in detail They are (i)relations among elements which organize the gathering orders andmethods of different collaborative elements (ii) relations amonglife cycle which present modeling processes and agility management and (iii) relations among levels which define relationshipsamong different levels of collaborative processes strategy operation and support This paper aims to explain the collaborativeknowledge framework and the relations inside

1 Introduction

The INTEROP-NOE proposes an enterprise interoperabilityframework which defined three interoperability barriersconceptual technological and organizational [1] (INTEROP-VLab the European Virtual Laboratory for Enterprise Inter-operability (I-VLab) is an initiative to develop networkedresearch with critical mass in the Enterprise Interoperabil-ity (EI) domain and associated domains (Future Internetand Enterprise Systems Applications) Created on March2007 as an AISBL (Association Internationale Sans ButLucratif) under Belgian law I-VLab coordinates now more50 institutions from 11 countries (including China) and over200 researchers httpwwwinterop-vlabeu) Consideringthat enterprisesrsquo information systems are the practical andoperational part in enterprise it is a crucial requirement tobreak technological barriers among enterprisesrsquo informationsystems There exists possibility of jumping organizationaland conceptual obstacles by crushing technological stum-bling block (Figure 1) To search for a method to break the

technological barriers among enterprisesrsquo information sys-tems various architectures for the interoperation of infor-mation systems are introduced and compared in [2] Theyinclude Peer-to-Peer [3] Standardization (Standardizationuses pivot canonical model or metamodel to reduce thenumber of translators (similar to Peer-to-Peer)) Federation(Federation derives from standardization and uses a globalstatic federated schema) Multibase (Multibase uses a singlelanguage for many ISs) Ontology [4] and Mediation [5]Considering the weak point of adding a new partner (andits IS (Information System)) which requires many translatorsfor each existing partner Peer-to-Peer and Standardizationare eliminated Considering the difficulty of building com-mon standard and language Federation and Multibase areremoved Although mediation information system (MIS)requires the difficult task of constructing automatically col-laborative process MIS still is a credible and pertinent wayof supporting ISs interoperability The concept of mediationwas first presented in this MIS should be able to deal with(Figure 1)

HindawiScientific ProgrammingVolume 2017 Article ID 9026387 18 pageshttpsdoiorg10115520179026387

2 Scientific Programming

Collaboration

Organizational barrier

Mediationinformation system

Technological barrier

Conceptualbarrier

Information systeminteroperability

Break barrier

Processorchestration

Serviceselection

Dataconversion

Figure 1 Framework of collaborative situation

Knowledge gathering

Process cartography

MIS deployment

Agility management

Model transformation

Model transformation

Detection

Adaptation

CIM to PIM

PIM to PSM

Controlling of agility

Figure 2 Global picture of MISE 20

(i) Service selection MIS selects services which areprovided by enterprise to achieve the collaborativegoal

(ii) Data conversion MIS transfers data among differententerprises to share business or technical informa-tion

(iii) Process orchestration MIS orchestrates the servicesshared by enterprises in process to transfer shareddata and complete collaboration

Since 2009 MISE 20 (Mediation Information SystemEngineering Version 20) project has been launched Theproject is Model-Driven Architecture (MDA) [6] and ServiceOriented Architecture (SOA) [7] based MDA is dividedinto several models According to [8] the models are Com-putation Independent Model (CIM) Platform IndependentModel (PIM) and Platform Specific Model (PSM) Based onMDA the global picture of MISE 20 is divided into several

parts (Figure 2) abstract level concrete level and agilitymanagement

Abstract level concerns the transformation from CIM toPIM in the design-time MIS This part of work is presentedin [9] It gathers basis collaborative knowledge gatheringand deduces the cartography of business collaborative pro-cess In this level the collaborative knowledge (eg partnerinformation collaborative objectives collaborative networkand partnersrsquo functions) is collected and presented by orga-nizational functional and informational models And thenthis knowledge is transferred into the cartography of collabo-rative process thanks to collaborative metamodel and modeltransformation rules

Concrete level concerns the transformation from PIM toPSM in the design time ofMISThis part of work is presentedin [22] It reuses the cartography of collaborative processand transfers it to the technical collaborative workflow Theworkflow is deployed on ESB [23] and developed as MIS

Scientific Programming 3

Agility management concerns the detection of errors inthe runtime of MIS and the adaption of CIM PIM and PSMto solve the problems This part of work is presented in [24]

Due to complexity of MISE 20 engineering the collab-orative knowledge framework is defined to classify collab-orative knowledge in abstract and concrete level Howeverabstract level engineering still contains models metamodeland model transformation mechanism They are correlatedand interacted with orders and individual processes In orderto clearly explain the engineering approach of MISE 20 andto help researchers and enterprises to reuse MISE 20 engi-neering approach the collaborative knowledge framework isbuilt In the collaborative knowledge framework the relationsof elements inside the framework are presented These rela-tions contain (i) relations among elements presenting modeland metamodels used to present or organize collaborativeknowledge which is defined in collaborative knowledgeframework (ii) relations among life cycle defining modelsrsquouse orders and modelsrsquo transformation processes and(iii) relations among levels providing messages transferredamong subcollaborative processes in collaborative businessprocess model

In this paper Section 2 first addresses existing enterprisearchitectures and interoperability frameworks Secondly itpresents collaborative situation framework Section 3 pro-vides explanation of abstract level frameworks relations ofcollaborative elements relations of collaborative life cycleand relations of collaborative levels Section 4 provides acase study This case study connects abstract level and con-crete level and shows the using of collaborative knowledgeframework Section 5 gives the evaluation of the collaborativeknowledge framework Section 6 draws some concludingremarks discusses the feasibility of our work and outlinesour future investigations

2 Collaborative SituationFramework Proposal

21 States of Art In general framework is a real or conceptualstructure intended to serve as a support or guide for thebuilding for something that expands the structure into some-thing useful A framework is a hypothetical description of acomplex entity or process According to Camarinha-Matosand Afsarmanesh ldquoin themodeling area a framework can beseen as an ldquoenveloperdquo thatmight include a number of (partial)models collections of templates procedures and methodsrules and even tools (eg modeling languages)rdquo [25]Model-ing framework provides a set of viewpoints of subject corre-lated organized and interacted An enterprise architectureframework is a framework for an enterprise architecturewhich defines how to organize the structure and viewsassociated with enterprise architecture

Enterprise architecture started with the Zachman Frame-work [26] in 1987 Another early implementation of an enter-prise architecture frameworkwas the ldquoTechnical ArchitectureFramework for Information Managementrdquo (TAFIM) [27]During 80s the most known enterprise architectures areas follows the Purdue Enterprise-Reference model PERA

(1991) Architecture of Integrated Information Systems ARIS(1991) the Computer Integrated Manufacturing Open Sys-tem Architecture CIMOSA (1993) the Open Group Archi-tecture Framework TOGAF (1995) the GIM architecture(1996) Enterprise-Reference Architecture and Methodol-ogy GERAM (1997) and Federal Enterprise ArchitectureFramework FEAF (1999) In 2003 DODAF (Department ofDefense Architecture Framework) [28] was developed bythe US Department of Defense DODAF is an evolutionaryupgrade of the C4ISR architecture framework [29] In 2005The British Ministry of Defense Architectural Framework(MODAF) v10 [30] was developed by MOD from DODAFversion 10

The Zachman Framework [31] is used for enterprise engi-neering andmanufacturing It provides the views from differ-ent members (eg planner owner and designer) and knowl-edge (data function and network) Zachman frameworkalmost covers all the knowledge of enterprise But the mainproblem is that there is no related methodology followed touse the framework and potential connections among viewsare ignored

The GIM (GRAI Integrated Methodology) architecture[32] is amodelingmethodology intended for general descrip-tion focused ondetails inmanufacturing control systemThisframework has four main parts functional model informa-tional model decision-making model and physical modelThe strong point of this framework is the decision-makingmodel GRAI [33] which allows user tomodel all the decisionunits and activities by time and organizationThe weak pointis that the framework considers information system as animportant part in enterprise without defining detailed con-nections with business part

PERA [34] considers that enterprise has three maincomponents facility organization and information systemIt manages these three components by different phases in lifecycle

Architecture of Integrated Information Systems ARIS[35] is architecture for information system integration whichis the most contiguous with the objective of MISE 20 ARISmanages integration by views data process function orga-nization and control The connections among views areconsidered also It also provides modeling tools and softwareplatform to support model building and process transfor-mation from business to technical But user must build thebusiness process The regretful point is that MDA modeltransformation phase is not shown in the framework

The Computer Integrated Manufacturing Open SystemArchitecture CIMOSA [36] is a three-dimension cube (gen-eration of views instantiation of building blocks and deriva-tion of models) The clear structure makes the frameworkeasy to understand Each dimension provides an angle forstarting enterprise modeling CIMOSA provides a processmodel without software supporting In CIMOSA it combinesfunction and process in the function viewWith the objectiveof computer integration it limits the further development ofweb services

The Open Group Architecture Framework TOGAF [28]is an industry standard architecture framework that may beused freely by any organization wishing to develop informa-tion systems architecture for use within that organization It

4 Scientific Programming

has been developed and continuously evolved In TOGAF v9(httpwwwopengrouporgtogaf) (2009) TOGAF Archi-tecture Development Method (ADM) is provided It is usedto manage the use process of all the subarchitectures (ADMGuidelines and Technique TOGAF Architecture Con-tent Framework Enterprise Continuum TOGAF ReferenceModels and TOGAF Capability Framework) in TOGAFAccording to TOGAF v9 survey results [37] more than50 organizations are using TOGAF 8 and 9 to managetheir enterprises (TOGAF 8 30 TOGAF 9 21 Zachman24 FEAF 7 DODAF 7 and MODAF 2) The scopeof the four architecture domains (data architecture (what)business architecture (how) technical architecture (where)and applications architecture (who)) of TOGAF aligns withthe first four rows (what how where and who but withoutwhen and why) of the Zachman Framework

Enterprise-Reference Architecture and MethodologyGERAM [38] provides a generalized framework for describ-ing the components needed in all types of enterprise engi-neeringenterprise integration processes The shining pointof this framework is life cycle GERA (generalized enterprise-reference architecture) classified generic concepts as humanoriented process oriented and technology oriented Theshining point is process oriented which defines enterpriselife cycle into enterprise engineering reengineering andredesign And then the framework even details views (modelcontent purpose implementation and manifestation) andobjects (customer service software hardware informationfunction machine human etc) on the life cycle TheGERAM framework defines the minimal set of elementswhich should be accompanied with to build enterprisearchitectures But these elements are abstract for exampleenterprise engineering methodologies modeling languagesand modeling methodology Users have to develop their ownspecific methodology or choose a developed methodology

Federal Enterprise Architecture Framework FEAF [39]provides a common methodology for information technol-ogy acquisition use and disposal in the Federal governmentIt provides performance reference model business referencemodel service component reference model data referencemodel and technical reference model

Except enterprise architectures in recent years theenterprise interoperability framework is developed IDEASInteroperability Development for Enterprise Application andSoftware (2003) [40]manages the enterprise integration frombusiness knowledge and application level by solving seman-tic problems AIF ATHENA interoperability framework(2007) [41] improves IDEAS It defines enterprise interoper-ability with four levels business service process and dataThe solutions of each level can be ontology semantics andmodel-driven interoperability EIF differs from IDEAS andAIF IDEAS and AIF are two-dimension frameworks EIFEnterprise Interoperability Framework (2008) [1] is three-dimension framework It defines enterprise interoperabilityfrom three angles interoperability approaches interoperabil-ity barriers and interoperability concerns

The architectures mentioned above have been summa-rized in Table 1

22 MISE 20 Collaborative Situation Framework The col-laborative situation framework should also cover all the

Collaborativesituation life cycle

steps

Collaborativesituation elements

Collaborativesituation levels

Strategy

Operation

Support

CIM PIM PSM Controlling

Organizational

InformationalFunctional

Process

Abstract Concrete

Figure 3 Framework of collaborative situation

collaborative knowledge and direct collaborative situationmodeling and helps mediation information system genera-tion In MISE 20 a collaborative framework should defineviewpoints by organization function information processand interconnections among them Furthermore the engi-neering approach of MISE 20 goes through all the steps ofMDA So in our framework two dimensions with viewpointsand MDA are confirmed

However almost all the frameworks mentioned in Sec-tion 21 have a module or a unit for strategy managementor decision-making which is not shown in the main frame-work Furthermore according to ISO 9000 [42 43] a busi-ness process should contain strategy process operation pro-cess and support process With our experience on MISE 10deployment one collaborative process is not good enough tomanage collaborative situation It is very hard to understandfor different levelsrsquo managers and workers So we break thetwo dimensions framework into 3 levels As shown in Fig-ure 3 it is MISE 20 collaborative knowledge framework

MISE 20 collaborative situation framework has threedimensions

(i) Collaborative situation life cycle steps separate collab-oration situation knowledge by mediation informa-tion system building steps The collaboration situa-tion life cycle covers CIM PIM PSM and controllingThe CIM and PIM are at the abstract level In theabstract level business information and collaborationrequirement have to be gathered With this infor-mation the business collaborative process may bededuced Then at the concrete level the problem ofsemantic web service may be additional at PSM andcontrolling stages In this part collaboration processand semantic information are used to build targetmediation information system

(ii) Collaborative situation levels separate collaborationsituation knowledge by different collaboration man-agement levels The dimension provides not only theoperation level but also the strategy and supportlevel The strategy level helps decision-making col-laboration direction choosing and management levelcommunicatingTheoperation level provides detailed

Scientific Programming 3

Agility management concerns the detection of errors inthe runtime of MIS and the adaption of CIM PIM and PSMto solve the problems This part of work is presented in [24]

Due to complexity of MISE 20 engineering the collab-orative knowledge framework is defined to classify collab-orative knowledge in abstract and concrete level Howeverabstract level engineering still contains models metamodeland model transformation mechanism They are correlatedand interacted with orders and individual processes In orderto clearly explain the engineering approach of MISE 20 andto help researchers and enterprises to reuse MISE 20 engi-neering approach the collaborative knowledge framework isbuilt In the collaborative knowledge framework the relationsof elements inside the framework are presented These rela-tions contain (i) relations among elements presenting modeland metamodels used to present or organize collaborativeknowledge which is defined in collaborative knowledgeframework (ii) relations among life cycle defining modelsrsquouse orders and modelsrsquo transformation processes and(iii) relations among levels providing messages transferredamong subcollaborative processes in collaborative businessprocess model

In this paper Section 2 first addresses existing enterprisearchitectures and interoperability frameworks Secondly itpresents collaborative situation framework Section 3 pro-vides explanation of abstract level frameworks relations ofcollaborative elements relations of collaborative life cycleand relations of collaborative levels Section 4 provides acase study This case study connects abstract level and con-crete level and shows the using of collaborative knowledgeframework Section 5 gives the evaluation of the collaborativeknowledge framework Section 6 draws some concludingremarks discusses the feasibility of our work and outlinesour future investigations

2 Collaborative SituationFramework Proposal

21 States of Art In general framework is a real or conceptualstructure intended to serve as a support or guide for thebuilding for something that expands the structure into some-thing useful A framework is a hypothetical description of acomplex entity or process According to Camarinha-Matosand Afsarmanesh ldquoin themodeling area a framework can beseen as an ldquoenveloperdquo thatmight include a number of (partial)models collections of templates procedures and methodsrules and even tools (eg modeling languages)rdquo [25]Model-ing framework provides a set of viewpoints of subject corre-lated organized and interacted An enterprise architectureframework is a framework for an enterprise architecturewhich defines how to organize the structure and viewsassociated with enterprise architecture

Enterprise architecture started with the Zachman Frame-work [26] in 1987 Another early implementation of an enter-prise architecture frameworkwas the ldquoTechnical ArchitectureFramework for Information Managementrdquo (TAFIM) [27]During 80s the most known enterprise architectures areas follows the Purdue Enterprise-Reference model PERA

(1991) Architecture of Integrated Information Systems ARIS(1991) the Computer Integrated Manufacturing Open Sys-tem Architecture CIMOSA (1993) the Open Group Archi-tecture Framework TOGAF (1995) the GIM architecture(1996) Enterprise-Reference Architecture and Methodol-ogy GERAM (1997) and Federal Enterprise ArchitectureFramework FEAF (1999) In 2003 DODAF (Department ofDefense Architecture Framework) [28] was developed bythe US Department of Defense DODAF is an evolutionaryupgrade of the C4ISR architecture framework [29] In 2005The British Ministry of Defense Architectural Framework(MODAF) v10 [30] was developed by MOD from DODAFversion 10

The Zachman Framework [31] is used for enterprise engi-neering andmanufacturing It provides the views from differ-ent members (eg planner owner and designer) and knowl-edge (data function and network) Zachman frameworkalmost covers all the knowledge of enterprise But the mainproblem is that there is no related methodology followed touse the framework and potential connections among viewsare ignored

The GIM (GRAI Integrated Methodology) architecture[32] is amodelingmethodology intended for general descrip-tion focused ondetails inmanufacturing control systemThisframework has four main parts functional model informa-tional model decision-making model and physical modelThe strong point of this framework is the decision-makingmodel GRAI [33] which allows user tomodel all the decisionunits and activities by time and organizationThe weak pointis that the framework considers information system as animportant part in enterprise without defining detailed con-nections with business part

PERA [34] considers that enterprise has three maincomponents facility organization and information systemIt manages these three components by different phases in lifecycle

Architecture of Integrated Information Systems ARIS[35] is architecture for information system integration whichis the most contiguous with the objective of MISE 20 ARISmanages integration by views data process function orga-nization and control The connections among views areconsidered also It also provides modeling tools and softwareplatform to support model building and process transfor-mation from business to technical But user must build thebusiness process The regretful point is that MDA modeltransformation phase is not shown in the framework

The Computer Integrated Manufacturing Open SystemArchitecture CIMOSA [36] is a three-dimension cube (gen-eration of views instantiation of building blocks and deriva-tion of models) The clear structure makes the frameworkeasy to understand Each dimension provides an angle forstarting enterprise modeling CIMOSA provides a processmodel without software supporting In CIMOSA it combinesfunction and process in the function viewWith the objectiveof computer integration it limits the further development ofweb services

The Open Group Architecture Framework TOGAF [28]is an industry standard architecture framework that may beused freely by any organization wishing to develop informa-tion systems architecture for use within that organization It

4 Scientific Programming

has been developed and continuously evolved In TOGAF v9(httpwwwopengrouporgtogaf) (2009) TOGAF Archi-tecture Development Method (ADM) is provided It is usedto manage the use process of all the subarchitectures (ADMGuidelines and Technique TOGAF Architecture Con-tent Framework Enterprise Continuum TOGAF ReferenceModels and TOGAF Capability Framework) in TOGAFAccording to TOGAF v9 survey results [37] more than50 organizations are using TOGAF 8 and 9 to managetheir enterprises (TOGAF 8 30 TOGAF 9 21 Zachman24 FEAF 7 DODAF 7 and MODAF 2) The scopeof the four architecture domains (data architecture (what)business architecture (how) technical architecture (where)and applications architecture (who)) of TOGAF aligns withthe first four rows (what how where and who but withoutwhen and why) of the Zachman Framework

Enterprise-Reference Architecture and MethodologyGERAM [38] provides a generalized framework for describ-ing the components needed in all types of enterprise engi-neeringenterprise integration processes The shining pointof this framework is life cycle GERA (generalized enterprise-reference architecture) classified generic concepts as humanoriented process oriented and technology oriented Theshining point is process oriented which defines enterpriselife cycle into enterprise engineering reengineering andredesign And then the framework even details views (modelcontent purpose implementation and manifestation) andobjects (customer service software hardware informationfunction machine human etc) on the life cycle TheGERAM framework defines the minimal set of elementswhich should be accompanied with to build enterprisearchitectures But these elements are abstract for exampleenterprise engineering methodologies modeling languagesand modeling methodology Users have to develop their ownspecific methodology or choose a developed methodology

Federal Enterprise Architecture Framework FEAF [39]provides a common methodology for information technol-ogy acquisition use and disposal in the Federal governmentIt provides performance reference model business referencemodel service component reference model data referencemodel and technical reference model

Except enterprise architectures in recent years theenterprise interoperability framework is developed IDEASInteroperability Development for Enterprise Application andSoftware (2003) [40]manages the enterprise integration frombusiness knowledge and application level by solving seman-tic problems AIF ATHENA interoperability framework(2007) [41] improves IDEAS It defines enterprise interoper-ability with four levels business service process and dataThe solutions of each level can be ontology semantics andmodel-driven interoperability EIF differs from IDEAS andAIF IDEAS and AIF are two-dimension frameworks EIFEnterprise Interoperability Framework (2008) [1] is three-dimension framework It defines enterprise interoperabilityfrom three angles interoperability approaches interoperabil-ity barriers and interoperability concerns

The architectures mentioned above have been summa-rized in Table 1

22 MISE 20 Collaborative Situation Framework The col-laborative situation framework should also cover all the

Collaborativesituation life cycle

steps

Collaborativesituation elements

Collaborativesituation levels

Strategy

Operation

Support

CIM PIM PSM Controlling

Organizational

InformationalFunctional

Process

Abstract Concrete

Figure 3 Framework of collaborative situation

collaborative knowledge and direct collaborative situationmodeling and helps mediation information system genera-tion In MISE 20 a collaborative framework should defineviewpoints by organization function information processand interconnections among them Furthermore the engi-neering approach of MISE 20 goes through all the steps ofMDA So in our framework two dimensions with viewpointsand MDA are confirmed

However almost all the frameworks mentioned in Sec-tion 21 have a module or a unit for strategy managementor decision-making which is not shown in the main frame-work Furthermore according to ISO 9000 [42 43] a busi-ness process should contain strategy process operation pro-cess and support process With our experience on MISE 10deployment one collaborative process is not good enough tomanage collaborative situation It is very hard to understandfor different levelsrsquo managers and workers So we break thetwo dimensions framework into 3 levels As shown in Fig-ure 3 it is MISE 20 collaborative knowledge framework

MISE 20 collaborative situation framework has threedimensions

(i) Collaborative situation life cycle steps separate collab-oration situation knowledge by mediation informa-tion system building steps The collaboration situa-tion life cycle covers CIM PIM PSM and controllingThe CIM and PIM are at the abstract level In theabstract level business information and collaborationrequirement have to be gathered With this infor-mation the business collaborative process may bededuced Then at the concrete level the problem ofsemantic web service may be additional at PSM andcontrolling stages In this part collaboration processand semantic information are used to build targetmediation information system

(ii) Collaborative situation levels separate collaborationsituation knowledge by different collaboration man-agement levels The dimension provides not only theoperation level but also the strategy and supportlevel The strategy level helps decision-making col-laboration direction choosing and management levelcommunicatingTheoperation level provides detailed

4 Scientific Programming

has been developed and continuously evolved In TOGAF v9(httpwwwopengrouporgtogaf) (2009) TOGAF Archi-tecture Development Method (ADM) is provided It is usedto manage the use process of all the subarchitectures (ADMGuidelines and Technique TOGAF Architecture Con-tent Framework Enterprise Continuum TOGAF ReferenceModels and TOGAF Capability Framework) in TOGAFAccording to TOGAF v9 survey results [37] more than50 organizations are using TOGAF 8 and 9 to managetheir enterprises (TOGAF 8 30 TOGAF 9 21 Zachman24 FEAF 7 DODAF 7 and MODAF 2) The scopeof the four architecture domains (data architecture (what)business architecture (how) technical architecture (where)and applications architecture (who)) of TOGAF aligns withthe first four rows (what how where and who but withoutwhen and why) of the Zachman Framework

Enterprise-Reference Architecture and MethodologyGERAM [38] provides a generalized framework for describ-ing the components needed in all types of enterprise engi-neeringenterprise integration processes The shining pointof this framework is life cycle GERA (generalized enterprise-reference architecture) classified generic concepts as humanoriented process oriented and technology oriented Theshining point is process oriented which defines enterpriselife cycle into enterprise engineering reengineering andredesign And then the framework even details views (modelcontent purpose implementation and manifestation) andobjects (customer service software hardware informationfunction machine human etc) on the life cycle TheGERAM framework defines the minimal set of elementswhich should be accompanied with to build enterprisearchitectures But these elements are abstract for exampleenterprise engineering methodologies modeling languagesand modeling methodology Users have to develop their ownspecific methodology or choose a developed methodology

Federal Enterprise Architecture Framework FEAF [39]provides a common methodology for information technol-ogy acquisition use and disposal in the Federal governmentIt provides performance reference model business referencemodel service component reference model data referencemodel and technical reference model

Except enterprise architectures in recent years theenterprise interoperability framework is developed IDEASInteroperability Development for Enterprise Application andSoftware (2003) [40]manages the enterprise integration frombusiness knowledge and application level by solving seman-tic problems AIF ATHENA interoperability framework(2007) [41] improves IDEAS It defines enterprise interoper-ability with four levels business service process and dataThe solutions of each level can be ontology semantics andmodel-driven interoperability EIF differs from IDEAS andAIF IDEAS and AIF are two-dimension frameworks EIFEnterprise Interoperability Framework (2008) [1] is three-dimension framework It defines enterprise interoperabilityfrom three angles interoperability approaches interoperabil-ity barriers and interoperability concerns

The architectures mentioned above have been summa-rized in Table 1

22 MISE 20 Collaborative Situation Framework The col-laborative situation framework should also cover all the

Collaborativesituation life cycle

steps

Collaborativesituation elements

Collaborativesituation levels

Strategy

Operation

Support

CIM PIM PSM Controlling

Organizational

InformationalFunctional

Process

Abstract Concrete

Figure 3 Framework of collaborative situation

collaborative knowledge and direct collaborative situationmodeling and helps mediation information system genera-tion In MISE 20 a collaborative framework should defineviewpoints by organization function information processand interconnections among them Furthermore the engi-neering approach of MISE 20 goes through all the steps ofMDA So in our framework two dimensions with viewpointsand MDA are confirmed

However almost all the frameworks mentioned in Sec-tion 21 have a module or a unit for strategy managementor decision-making which is not shown in the main frame-work Furthermore according to ISO 9000 [42 43] a busi-ness process should contain strategy process operation pro-cess and support process With our experience on MISE 10deployment one collaborative process is not good enough tomanage collaborative situation It is very hard to understandfor different levelsrsquo managers and workers So we break thetwo dimensions framework into 3 levels As shown in Fig-ure 3 it is MISE 20 collaborative knowledge framework

MISE 20 collaborative situation framework has threedimensions

(i) Collaborative situation life cycle steps separate collab-oration situation knowledge by mediation informa-tion system building steps The collaboration situa-tion life cycle covers CIM PIM PSM and controllingThe CIM and PIM are at the abstract level In theabstract level business information and collaborationrequirement have to be gathered With this infor-mation the business collaborative process may bededuced Then at the concrete level the problem ofsemantic web service may be additional at PSM andcontrolling stages In this part collaboration processand semantic information are used to build targetmediation information system

(ii) Collaborative situation levels separate collaborationsituation knowledge by different collaboration man-agement levels The dimension provides not only theoperation level but also the strategy and supportlevel The strategy level helps decision-making col-laboration direction choosing and management levelcommunicatingTheoperation level provides detailed

Scientific Programming 5

Table 1 Summary of enterprise architectures

Framework Type Update Completeness Practicability Toolsupport

Methodsupport Summary

Zachman(1987) EA 2011

V3 Middle Low No No A general framework without specification

GIM(1988) EA-PM No Middle Middle No Yes Develop a useful decision making method GRAI

PERA(1991) EA No Middle Middle No No Consider enterprise as facility organization and

information system

ARIS(1991) EIA-IS 2011

V72 Middle High Yes YesMDA and SOA based consider enterprise

integration views as organization data functionprocess and control

CIMOSA(1993) EIA No Middle Middle No Yes Clear structured three-dimension framework

which are views models and levelsTOGAF(1995) EA-IS 2009

V9 High High No Yes Architecture of architectures each part is welldetailed

GERA(1997) EA No High Low No Yes Enterprise engineering life cycle is well detailed

FEA (1999) EA-IS 2012V3 High High No Yes

Organize enterprise by levels business designapplication and technology containing as-is and

to-be system modeling

DoDAF(2003) EA-IS 2009

V20 High Middle No YesSeparates enterprise by viewpoints all data andinformation standards capability operational

services systems and project

IDEAS(2003) EF No Low Low No No

Defines interoperability levels businessknowledge and application The solution is

semantics

AIF (2007) EF No Middle Middle No NoDefines interoperability levels business serviceprocess and data The solutions are ontologysemantics and model-driven interoperability

EIF (2008) EF No High Middle No NoDefines interoperability from interoperability

concerns interoperability barriers andinteroperability approaches

EA enterprise architecture EIA enterprise integration architecture EF enterprise interoperability framework IS information system PM productmanufacturing

collaboration solutions and execution results Thesupport level complements need and functions foroperation level and strategy level

(iii) Collaborative situation elements separate the col-laboration situation knowledge by different knowl-edge viewpoints It covers the organizational viewthe informational view the process view and thefunctional view The organizational view concernscollaboration network partners and collaborativeobjectiveThe informational view provides basic busi-ness data Process view provides collaboration pro-cess The functional view provides the capabilities ofeach partner

The goal of collaborative situation framework is to transferorganizational functional and informational elements ofCIM level to process element (which presents the process asstrategy operation and support process) in PIM level

3 Abstract Level Architecture Specification

Collaborative situation framework clearly shows the knowl-edge which should be gathered in abstract level But thisframework could not answer which knowledge should begathered first What are the connections among the knowl-edgeWhat kinds ofmodels tools or languages could be usedto present the knowledge to user

MISE 20 also proposes the following detailed architec-tures

(i) Relations among elements provide models which areused to present or organize abstract level knowledgeand basis connections

(ii) Relations among life cycle provide how are thesemodels played transferred and built to deduce col-laborative process

(iii) Relations among levels define three kinds ofmessageswhich are used to trigger another process

6 Scientific Programming

(1) Organizational

(2) Functional

(3) Informational

(4) Process

Gather collaborative networkpartners partnersrsquo relationshipsand objectives

Gather partnersrsquo functions whichcorrespond to objectives inorganizational view

Gather detailed attributes formessage mentioned in functionalview

Reorganize above knowledge todeduce collaborative process

Organizationalmodel

Functionalmodel

Informationalmodel

Processmodel Model

transformationrules

Ontologymetamodel

(3) InformationalGather detailed attributes formessage mentioned in functionalview

Informationalmodel

Organizationalconcepts

Functionalconcepts

Informationalconcepts

Processconcepts

Figure 4 Relations among collaborative situation elements

31 Relations among Elements Relations of collaborative ele-ments (RCE) are based on Collaborative Knowledge Frame-work Abstract level The RCE aims at (i) defining modelingmethods or modeling languages to gather or organize thecollaborative knowledge at abstract level which is definedin collaborative situation framework and (ii) providing thegathering orders of collaborative elements at the abstractlevel As shown in Figure 4 the RCE has two parts (i)organizational functional informational and process and(ii) models and metamodel (and ontology) In MISE 20there exists an order which should be followed when thecollaborative elements are gathered

When the collaboration starts the first thing to know isthe following what are the objectives And who are the part-ners The organizational elements should be gathered firstFor these elements collaborative network partners partnersrsquorelationships and objectives of network and partners aregathered All the knowledge of organizational element isthe initial knowledge for a collaborative situation In orderto gather the organizational elements an organizationalmodel is necessary to gather and present the organizationalknowledge

In organizational elements the objectives and the part-ners of the collaboration are providedThen the next thing toknow is the following if the partners are willing to involve inthe collaboration what are the functions of partners Whichfunctions could be used to achieve the identified objectivesSo the functional elements should be gathered second Forthis element partnersrsquo functions have been gathered In orderto fix this requirement a functional model is required togather partnersrsquo functions

Even though normally a functional model does not justgather functional information it also covers inputoutput

messages which are exchanged among functions In somecase the inputoutput messages of functional model do notcontain enough informational knowledge An informationalmodel may be necessary to gather additional informationalknowledge to complete the collaborative knowledge Theadditional knowledge of informational knowledge may pro-vide the attributes ofmessages the relations amongmessagesand semantic annotationThe third elements to gather are theinformational elements

Finally all the information which has been gathered bythe above three types of elements is reused reorganizedand represented to deduce a collaborative process modelThis collaborative process model is based on BPMN ThisBPMN based collaborative process model is specialized toone mediation pool (containing three collaborative lanesstrategy process operation process and support process) andseveral partnersrsquo pools In order to transfer organizationalfunctional and informational elements as process elementthe definitions of models cannot accomplish the transforma-tion The modeling elements of organizational functionalinformational and process models should be managed andconfirmed by metamodel or ontology Based on ontologyand metamodel transformation rules could be defined totransfer organizational functional and informationalmodelsto processmodel InMISE 20 the collaborative ontology andthe model transformation rules are defined to complete thismission

32 Relations among Life Cycles In the collaborative situationframework the collaborative situation life cycle containsCIM PIM PSM and controlling In the collaborative situ-ation framework reader could understand them as follows

Scientific Programming 7

CIM

PIM

PSM

Businessknowledge

Technicalknowledge

Controlling

2nd cycle

1st cycle

Web serviceworkflow

Figure 5 Relations in collaborative situation life cycle

the collaborative situation life cycle starts with the CIM andmoves from the CIM to the PIM and from the PIM to thePSMThe controlling helps to go back to the CIM and to startover a new cycle But the dimension of collaborative situationlife cycle is not that simple The dimension could be openedand presented in a much more complex way In order topresent the dimensions correctly the relations of collabora-tive life cycle (RCC) are defined (Figure 5)

As presented in the collaborative situation frameworkthe dimension of life cycle is separated as four layers CIMPIM PSM and controllingTheRCC in Figure 3 also containsthese four layers The CIM present or define the gatheredcollaborative knowledge The knowledge of CIM is businessknowledge But the knowledge of PIM is technical knowl-edge In order to move from the CIM to the PIM there isa gap to fix The gap is to add the technical knowledge andtransfer from the CIM to the PIM After gathering technicalknowledge the life cycle moves from the CIM to the PIM

The knowledge of the PIM contains technical functionsof each partner But technical functions are not web servicesThe technical functions have to be implemented or executedby web services Semantic web service is the next gap to fixThen the PIM is transferred to the PSMThe life cycle movesfrom the PIM to the PSMThe PSM is deployed as mediationinformation system (MIS) at runtime (it is an ESB system toorchestrate BPEL file)Though theMIS is launched to invokethe whole collaborative process there may be several kindsof failures and errors at runtimeThis leads to the last layer oflife cycle the controlling The controlling is a layer to decidewhich layers of design-time life cycle should be redone topoint against the specific failures or changes at runtime TheRCC defines two kinds of life cycle

(i) The first life cycle goes back to the PIM layer It isdesigned to solve the failures of technical knowledgeFor example if the web service of one technicalfunction is down the semantic web service has tobe redone to select new web services which couldimplement the technical function

(ii) The second life cycle goes back to the CIM layer Itis designed to correct the mistakes of business knowl-edge For example if a new partner entered thecollaborative situation or a partner is no longer avail-able for the collaborative situation the life cycle has

Strategy level

Operation level

Support level

Feedback infoObjective info

Mean infoFeedback info

Obj

ectiv

e inf

o

Mea

n in

fo

Figure 6 Relations among collaborative situation levels

to restart all over from the beginning to collect thecorrect business information

33 Relations among Levels We have mentioned in previoussection all the models which have been defined in the RCEcover strategy operation and support level There are tworeasons to define these three levels First ISO 9000 [42] hasseparated business process into three types strategy opera-tion and support Second in MISE 10 [44 45] the collabo-rative process only covers operation level With the practicalexperience of research projects operation process is notenough for a collaborative situation which involves decision-making and resource supporting As the results of processdeduction architecture strategy operation and support col-laborative processes are generated But we do not knowwhat are the communications among these processes Howcould strategy process trigger an operation process Howcould a support process complete an operation process Inorder to answer these questions the relations of collaborativelevels (RCL) are defined to manage communications amongdifferent collaborative processes

The communications among strategy level operationlevel and support level have been shown in Figure 6 Among

8 Scientific Programming

these three levels three kinds ofmessages have been involvedobjective information feedback information and mean

(i) Objective information objective is the goal which isintended to attain Objective information is a mes-sage which contains the decision result of strategylevelThe objective information could be sent to oper-ation and support level The operation level and thesupport level invoke homologous process and usefulinformation to attain the goal in objective informa-tion

(ii) Feedback information feedback information is amessage which contains the operation level resultThe feedback information is sent from operation levelto strategy level It is used to report the operationalexception error result and so on Feedback informa-tion could also be sent fromoperation level to supportlevel This kind of feedback information is used totrigger or direct support process

(iii) Mean in the collaboration situation mean is a mes-sage which could contain any kind of information Itcould be an exception an error a feedback or a signal

4 Case Study

The knowledge framework presented in this paper is usedto develop MISE 20 project This project aims to deduceautomatically mediation information system to orchestratethe collaborative process among organizations The method-ology to develop MISE 20 project has been presented in [4647] In this section we will present the use of collaborativeknowledge framework through a small collaborative caseand each step of the case used the methodology presentedin [46 47] but here we are not focusing on the method butthe use result of the framework so the case only shows theresults of CIM PIM and PSMControlling phase is presentedin [48] it is not detailed in this case

41 CIM Organizational Functional and InformationalModel Development [9 47] The knowledge in this phasecovers the target collaborative situation In the work ofDr Rajsiri et al [44] the initial knowledge is structuredaccording to collaborative network partners and commongoal In the work of Dr Truptil et al [49] the sharedfunctions of partners are added to the initial knowledgeThe above two results are combined together and improvedin the methodology The collaborative network model andfunction model represent and define the initial collaborativesituation It covers the CIM organizational functional andinformational knowledge involved strategyoperationsupportlevels

The collaborative network model (Figures 7 and 8) doesnot only collect the collaborative network partners andpartner relations but also collect subcollaborative networkand collaborative objectives The objective of collaborationis classified into three types strategy objective operationobjective and support objective

The function model (Figure 9) is defined based on IDEF1 It represents the information concerning shared partnerfunctions and inputoutput messages

42 PIM ProcessModel Transformation [9 47] In this phasethe collaborative ontology and transformation rules aredefined to transfer the collaboration concepts to the medi-ation concepts in the collaborative ontology meanwhile (i)transfer CIM to PIM and (ii) transfer organizational informa-tional and functional knowledge to process knowledge Thereare five groups of transformation rules create mediatorcreate mediator relationship create generatedmediator func-tion link generatedmediator function tomediator and createintermediator function Table 2 provides two equations ofgroup 1 and group 2 as examples of transformation rules(equations in total 11) With the transformation rules themediation concepts are deduced but there is not enoughknowledge for the extraction of collaborative process so thenext phase comes

The knowledge of this phase presents the matchingbetween objective and functions In this phase one method-ology is developed business service selection to choosefunctions to achieve objectives by linking the functions andobjectives to the instances of the collaborative ontology byusing ldquosame asrdquo and ldquonearbyrdquo relations This part of work isdetailed in [50] Figure 10 shows the interface in mediatormodeling tool which defines the ldquosame asrdquo and ldquonearbyrdquo rela-tions

For the method of process sequence deduction the link-age of inputoutputmessages and the objective basedmethodare mixed to deduce the sequences and the gateways Firstthe linkage of inputoutputmessages among functions is usedto get at global picture of the process Second the specialplace (the gateways are needed) of the global picture is takenand redone by using the objective based method Finallythe linkage of messages checks the results of objective basedmethod to get the best solution

The knowledge covers the collaborative process extrac-tion and sequencegateway deduction In this phase thededuction rules are defined to extract the collaborativeprocess cartography (Figure 11) and collaborative processes(Figure 19) To complete the sequence and the gateway themethod of sequence deduction is developed

43 PSM Technical Process Transformation [22 47] Thefirst task of PSM is to match web services with businessfunctions It covers organizational (web service provider)functional and informational knowledge in PSM with strat-egyoperationsupport levels Whereas a lot of annotationmechanisms exist for web services the recent BPMN 20 isstill devoid of a semantic standard However in addition toa higher design range (from very high level processes to exe-cutable workflows) this secondmajor version brings an XMLrepresentation and its extension mechanism Therefore wedecided to propose our own annotation mechanism calledSA-BPMN 20This extension adds two XML tags (i) Seman-ticDetails allows user to describe any activity requirement Itembeds both functional and internal behaviour description

Scientific Programming 9

Figure 7 Define organizational model

Figure 8 Define organizational model

Each one contains a name and a list ofURIs (corresponding tosemantic concepts fromany ontology) (ii) SemanticElementsaims at describing messages and sequencing flows attach-ing a list of expected messages or elements Each elementthen contains the syntactic name coupled with a list ofconcepts

To simplify semantic annotation the modeling platformembeds annotation tools to allow users to add or edit seman-tic concept references directly from the business processview (see Figure 12) Semantic concepts come from partnersrsquobusiness ontologies developed from scratch or based onMISErsquos one

10 Scientific Programming

Figure 9 Define functional model

Figure 10 Select ldquosame asrdquo and ldquonearbyrdquo instances

Table 2 Examples of transformation rules

Group 1 create mediatorSubnetworkrarrmediator

forallSub Network (X) (forallhasPartner (Sub Network (X) Partner (X1)) and (forallhasPartner (Sub Network (X) Partner (X2))and sdot sdot sdot and

(forallhasPartner (Sub Network (X) Partner (Xn))) (1)997888rarr existMediator (X) andexisthasMediator (Sub Network (X) Mediator (X))

Group 2 create mediator relationshipStrategy and operation objectiverarrmain functionrarr business messagerarr order

If forallStrategy Objective (X1) (forallgenerates (Strategy Objective (X1) Main Function (X1))) and

(2)

forallOperation Objective (X2) (forallgenerates (Operation Objective (X2) Main Function (X2)))If forallMain Function (X1) (forallout (Main Function (X1) Business Message (m))) andforallMain Function (X2) (forallin (Main Function (X2) Business Message (m)))997888rarr exist Order (m) (hasMediatorRelationship (Mediator (X1) Order (m))) andexist Order (m) (hasMediatorRelationship (Mediator (X2) Order (m)))

Scientific Programming 11

Figure 11 Extract process cartography

Figure 12 Semantic annotation of business process (SA-BPMN 20)

Once business processes annotated we aim at matchingbusiness activity semantic descriptions with technical serviceones The proposed approach is based on a ldquo1-to-1rdquo hybridmatchmaking mechanism and focuses on semantic compari-son Semantic distance between profiles is performed thanksto a logic-based reasoning coupled with a syntactic similaritymeasurement These measurements use information from

operation (service capability or activity requirement) andIO In order to perform this service composition anddespite granularity difference of models to match we use asemantic profileThis profile (represented in Figure 13) allowsus to describe the functional aspects of models It is filledwith semantic annotation from business activities (usingour SA-BPMN 20 mechanism) or technical services (using

12 Scientific Programming

Partner

Belongs to

Function

SemanticProfile

SemanticFunction SemanticElement

SemanticPartName stringConcepts ListltURlgt

Input

Output

Required bool

Child

InternalBehavior

UnitFunction

01

01

01

Follows0

lowast

0lowast

0lowast

01

01

01

01

01

01

1lowast

Figure 13 UML model of our semantic profile

SAWSDL or WSMO-Lite for now) This profile also embedsan internal behaviour description composed of a sequence ofunit activities Each of these unit activities is represented by alist of semantic concepts such as functional descriptionThispart enables description of business or technical sets in orderto facilitate service composition

Using syntactic and semantic information from businessand technical profiles our matchmaking mechanism thencomputes semantic and syntactic distance between modelsIn this view we first perform a ldquo1-to-1rdquo service matchingcomparing semantic concepts and names from both activitiesand web services profiles If no service fits business require-ments of the target activity we then try to respond tothe request using a set of services In order to do so weselect the closest technical service and then deduce a newresearch profile containing uncovered business conceptsThis new profile called complementary profile correspondsto remaining business requirements if we use this first webservice At this time we perform a new service matchingusing this profile and then compute the distance between theproposed sets of services and the initial business activityin order to propose ldquo1-to-119899rdquo matching results to users Thismechanism is performedwith several sets of possible servicesand activities using smart stopping conditions in order tosuggest the best results to user while avoiding combinatorialproblems

Finally service composition results are proposed to userfor validation or selection Figure 20 shows the dedicatedinterface which provides rated results (on the left) for eachactivity or set of activities (on the right)

Once the user has selected technical services we can focuson real data mapping The discovery of web services that fitour functional needs is not enough to generate executableprocesses and ensure good communication between partners

IS We also have to provide interoperability between theseservices

Semantic business information is not sufficient for mes-sage matchmaking One business concept such as a date canbe expressed in many formats (XML date time US dateformat etc)This choice belongs to the service developerwhocan also use classic XML date time declared as such in theservice description or choose to use an exotic one declaredas a simple string In order to solve this problem we proposea technical ontology focused on format concepts and linkedto technical databases filled with syntax representation andconversion formulae

Thanks to semantic and technical data description ofinvolved messages we generate data transformations usingthree main steps for each chosen service

(i) First we search for available outputs using processlogicWe have to find out which previous outputmes-sages can be used to create our input target message

(ii) Then using this available data we try to computethe whole message transformation using semanticlinks between tags format descriptions and technicalinformation about known transformations

(iii) If the whole message is not covered by the computedtransformation we first try to find an available trans-formation service using our service matchmakingmechanism described above We then submit resultsto the user for validation or completion

Once all transformations are validated or completedour concrete level management mechanism generates theexecutable workflow (using BPEL or BPMN 20 languagedepending on targeted execution engine) Links betweenbusiness activities and composed technical services are stored

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

6 Scientific Programming

(1) Organizational

(2) Functional

(3) Informational

(4) Process

Gather collaborative networkpartners partnersrsquo relationshipsand objectives

Gather partnersrsquo functions whichcorrespond to objectives inorganizational view

Gather detailed attributes formessage mentioned in functionalview

Reorganize above knowledge todeduce collaborative process

Organizationalmodel

Functionalmodel

Informationalmodel

Processmodel Model

transformationrules

Ontologymetamodel

(3) InformationalGather detailed attributes formessage mentioned in functionalview

Informationalmodel

Organizationalconcepts

Functionalconcepts

Informationalconcepts

Processconcepts

Figure 4 Relations among collaborative situation elements

31 Relations among Elements Relations of collaborative ele-ments (RCE) are based on Collaborative Knowledge Frame-work Abstract level The RCE aims at (i) defining modelingmethods or modeling languages to gather or organize thecollaborative knowledge at abstract level which is definedin collaborative situation framework and (ii) providing thegathering orders of collaborative elements at the abstractlevel As shown in Figure 4 the RCE has two parts (i)organizational functional informational and process and(ii) models and metamodel (and ontology) In MISE 20there exists an order which should be followed when thecollaborative elements are gathered

When the collaboration starts the first thing to know isthe following what are the objectives And who are the part-ners The organizational elements should be gathered firstFor these elements collaborative network partners partnersrsquorelationships and objectives of network and partners aregathered All the knowledge of organizational element isthe initial knowledge for a collaborative situation In orderto gather the organizational elements an organizationalmodel is necessary to gather and present the organizationalknowledge

In organizational elements the objectives and the part-ners of the collaboration are providedThen the next thing toknow is the following if the partners are willing to involve inthe collaboration what are the functions of partners Whichfunctions could be used to achieve the identified objectivesSo the functional elements should be gathered second Forthis element partnersrsquo functions have been gathered In orderto fix this requirement a functional model is required togather partnersrsquo functions

Even though normally a functional model does not justgather functional information it also covers inputoutput

messages which are exchanged among functions In somecase the inputoutput messages of functional model do notcontain enough informational knowledge An informationalmodel may be necessary to gather additional informationalknowledge to complete the collaborative knowledge Theadditional knowledge of informational knowledge may pro-vide the attributes ofmessages the relations amongmessagesand semantic annotationThe third elements to gather are theinformational elements

Finally all the information which has been gathered bythe above three types of elements is reused reorganizedand represented to deduce a collaborative process modelThis collaborative process model is based on BPMN ThisBPMN based collaborative process model is specialized toone mediation pool (containing three collaborative lanesstrategy process operation process and support process) andseveral partnersrsquo pools In order to transfer organizationalfunctional and informational elements as process elementthe definitions of models cannot accomplish the transforma-tion The modeling elements of organizational functionalinformational and process models should be managed andconfirmed by metamodel or ontology Based on ontologyand metamodel transformation rules could be defined totransfer organizational functional and informationalmodelsto processmodel InMISE 20 the collaborative ontology andthe model transformation rules are defined to complete thismission

32 Relations among Life Cycles In the collaborative situationframework the collaborative situation life cycle containsCIM PIM PSM and controlling In the collaborative situ-ation framework reader could understand them as follows

Scientific Programming 7

CIM

PIM

PSM

Businessknowledge

Technicalknowledge

Controlling

2nd cycle

1st cycle

Web serviceworkflow

Figure 5 Relations in collaborative situation life cycle

the collaborative situation life cycle starts with the CIM andmoves from the CIM to the PIM and from the PIM to thePSMThe controlling helps to go back to the CIM and to startover a new cycle But the dimension of collaborative situationlife cycle is not that simple The dimension could be openedand presented in a much more complex way In order topresent the dimensions correctly the relations of collabora-tive life cycle (RCC) are defined (Figure 5)

As presented in the collaborative situation frameworkthe dimension of life cycle is separated as four layers CIMPIM PSM and controllingTheRCC in Figure 3 also containsthese four layers The CIM present or define the gatheredcollaborative knowledge The knowledge of CIM is businessknowledge But the knowledge of PIM is technical knowl-edge In order to move from the CIM to the PIM there isa gap to fix The gap is to add the technical knowledge andtransfer from the CIM to the PIM After gathering technicalknowledge the life cycle moves from the CIM to the PIM

The knowledge of the PIM contains technical functionsof each partner But technical functions are not web servicesThe technical functions have to be implemented or executedby web services Semantic web service is the next gap to fixThen the PIM is transferred to the PSMThe life cycle movesfrom the PIM to the PSMThe PSM is deployed as mediationinformation system (MIS) at runtime (it is an ESB system toorchestrate BPEL file)Though theMIS is launched to invokethe whole collaborative process there may be several kindsof failures and errors at runtimeThis leads to the last layer oflife cycle the controlling The controlling is a layer to decidewhich layers of design-time life cycle should be redone topoint against the specific failures or changes at runtime TheRCC defines two kinds of life cycle

(i) The first life cycle goes back to the PIM layer It isdesigned to solve the failures of technical knowledgeFor example if the web service of one technicalfunction is down the semantic web service has tobe redone to select new web services which couldimplement the technical function

(ii) The second life cycle goes back to the CIM layer Itis designed to correct the mistakes of business knowl-edge For example if a new partner entered thecollaborative situation or a partner is no longer avail-able for the collaborative situation the life cycle has

Strategy level

Operation level

Support level

Feedback infoObjective info

Mean infoFeedback info

Obj

ectiv

e inf

o

Mea

n in

fo

Figure 6 Relations among collaborative situation levels

to restart all over from the beginning to collect thecorrect business information

33 Relations among Levels We have mentioned in previoussection all the models which have been defined in the RCEcover strategy operation and support level There are tworeasons to define these three levels First ISO 9000 [42] hasseparated business process into three types strategy opera-tion and support Second in MISE 10 [44 45] the collabo-rative process only covers operation level With the practicalexperience of research projects operation process is notenough for a collaborative situation which involves decision-making and resource supporting As the results of processdeduction architecture strategy operation and support col-laborative processes are generated But we do not knowwhat are the communications among these processes Howcould strategy process trigger an operation process Howcould a support process complete an operation process Inorder to answer these questions the relations of collaborativelevels (RCL) are defined to manage communications amongdifferent collaborative processes

The communications among strategy level operationlevel and support level have been shown in Figure 6 Among

8 Scientific Programming

these three levels three kinds ofmessages have been involvedobjective information feedback information and mean

(i) Objective information objective is the goal which isintended to attain Objective information is a mes-sage which contains the decision result of strategylevelThe objective information could be sent to oper-ation and support level The operation level and thesupport level invoke homologous process and usefulinformation to attain the goal in objective informa-tion

(ii) Feedback information feedback information is amessage which contains the operation level resultThe feedback information is sent from operation levelto strategy level It is used to report the operationalexception error result and so on Feedback informa-tion could also be sent fromoperation level to supportlevel This kind of feedback information is used totrigger or direct support process

(iii) Mean in the collaboration situation mean is a mes-sage which could contain any kind of information Itcould be an exception an error a feedback or a signal

4 Case Study

The knowledge framework presented in this paper is usedto develop MISE 20 project This project aims to deduceautomatically mediation information system to orchestratethe collaborative process among organizations The method-ology to develop MISE 20 project has been presented in [4647] In this section we will present the use of collaborativeknowledge framework through a small collaborative caseand each step of the case used the methodology presentedin [46 47] but here we are not focusing on the method butthe use result of the framework so the case only shows theresults of CIM PIM and PSMControlling phase is presentedin [48] it is not detailed in this case

41 CIM Organizational Functional and InformationalModel Development [9 47] The knowledge in this phasecovers the target collaborative situation In the work ofDr Rajsiri et al [44] the initial knowledge is structuredaccording to collaborative network partners and commongoal In the work of Dr Truptil et al [49] the sharedfunctions of partners are added to the initial knowledgeThe above two results are combined together and improvedin the methodology The collaborative network model andfunction model represent and define the initial collaborativesituation It covers the CIM organizational functional andinformational knowledge involved strategyoperationsupportlevels

The collaborative network model (Figures 7 and 8) doesnot only collect the collaborative network partners andpartner relations but also collect subcollaborative networkand collaborative objectives The objective of collaborationis classified into three types strategy objective operationobjective and support objective

The function model (Figure 9) is defined based on IDEF1 It represents the information concerning shared partnerfunctions and inputoutput messages

42 PIM ProcessModel Transformation [9 47] In this phasethe collaborative ontology and transformation rules aredefined to transfer the collaboration concepts to the medi-ation concepts in the collaborative ontology meanwhile (i)transfer CIM to PIM and (ii) transfer organizational informa-tional and functional knowledge to process knowledge Thereare five groups of transformation rules create mediatorcreate mediator relationship create generatedmediator func-tion link generatedmediator function tomediator and createintermediator function Table 2 provides two equations ofgroup 1 and group 2 as examples of transformation rules(equations in total 11) With the transformation rules themediation concepts are deduced but there is not enoughknowledge for the extraction of collaborative process so thenext phase comes

The knowledge of this phase presents the matchingbetween objective and functions In this phase one method-ology is developed business service selection to choosefunctions to achieve objectives by linking the functions andobjectives to the instances of the collaborative ontology byusing ldquosame asrdquo and ldquonearbyrdquo relations This part of work isdetailed in [50] Figure 10 shows the interface in mediatormodeling tool which defines the ldquosame asrdquo and ldquonearbyrdquo rela-tions

For the method of process sequence deduction the link-age of inputoutputmessages and the objective basedmethodare mixed to deduce the sequences and the gateways Firstthe linkage of inputoutputmessages among functions is usedto get at global picture of the process Second the specialplace (the gateways are needed) of the global picture is takenand redone by using the objective based method Finallythe linkage of messages checks the results of objective basedmethod to get the best solution

The knowledge covers the collaborative process extrac-tion and sequencegateway deduction In this phase thededuction rules are defined to extract the collaborativeprocess cartography (Figure 11) and collaborative processes(Figure 19) To complete the sequence and the gateway themethod of sequence deduction is developed

43 PSM Technical Process Transformation [22 47] Thefirst task of PSM is to match web services with businessfunctions It covers organizational (web service provider)functional and informational knowledge in PSM with strat-egyoperationsupport levels Whereas a lot of annotationmechanisms exist for web services the recent BPMN 20 isstill devoid of a semantic standard However in addition toa higher design range (from very high level processes to exe-cutable workflows) this secondmajor version brings an XMLrepresentation and its extension mechanism Therefore wedecided to propose our own annotation mechanism calledSA-BPMN 20This extension adds two XML tags (i) Seman-ticDetails allows user to describe any activity requirement Itembeds both functional and internal behaviour description

Scientific Programming 9

Figure 7 Define organizational model

Figure 8 Define organizational model

Each one contains a name and a list ofURIs (corresponding tosemantic concepts fromany ontology) (ii) SemanticElementsaims at describing messages and sequencing flows attach-ing a list of expected messages or elements Each elementthen contains the syntactic name coupled with a list ofconcepts

To simplify semantic annotation the modeling platformembeds annotation tools to allow users to add or edit seman-tic concept references directly from the business processview (see Figure 12) Semantic concepts come from partnersrsquobusiness ontologies developed from scratch or based onMISErsquos one

10 Scientific Programming

Figure 9 Define functional model

Figure 10 Select ldquosame asrdquo and ldquonearbyrdquo instances

Table 2 Examples of transformation rules

Group 1 create mediatorSubnetworkrarrmediator

forallSub Network (X) (forallhasPartner (Sub Network (X) Partner (X1)) and (forallhasPartner (Sub Network (X) Partner (X2))and sdot sdot sdot and

(forallhasPartner (Sub Network (X) Partner (Xn))) (1)997888rarr existMediator (X) andexisthasMediator (Sub Network (X) Mediator (X))

Group 2 create mediator relationshipStrategy and operation objectiverarrmain functionrarr business messagerarr order

If forallStrategy Objective (X1) (forallgenerates (Strategy Objective (X1) Main Function (X1))) and

(2)

forallOperation Objective (X2) (forallgenerates (Operation Objective (X2) Main Function (X2)))If forallMain Function (X1) (forallout (Main Function (X1) Business Message (m))) andforallMain Function (X2) (forallin (Main Function (X2) Business Message (m)))997888rarr exist Order (m) (hasMediatorRelationship (Mediator (X1) Order (m))) andexist Order (m) (hasMediatorRelationship (Mediator (X2) Order (m)))

Scientific Programming 11

Figure 11 Extract process cartography

Figure 12 Semantic annotation of business process (SA-BPMN 20)

Once business processes annotated we aim at matchingbusiness activity semantic descriptions with technical serviceones The proposed approach is based on a ldquo1-to-1rdquo hybridmatchmaking mechanism and focuses on semantic compari-son Semantic distance between profiles is performed thanksto a logic-based reasoning coupled with a syntactic similaritymeasurement These measurements use information from

operation (service capability or activity requirement) andIO In order to perform this service composition anddespite granularity difference of models to match we use asemantic profileThis profile (represented in Figure 13) allowsus to describe the functional aspects of models It is filledwith semantic annotation from business activities (usingour SA-BPMN 20 mechanism) or technical services (using

12 Scientific Programming

Partner

Belongs to

Function

SemanticProfile

SemanticFunction SemanticElement

SemanticPartName stringConcepts ListltURlgt

Input

Output

Required bool

Child

InternalBehavior

UnitFunction

01

01

01

Follows0

lowast

0lowast

0lowast

01

01

01

01

01

01

1lowast

Figure 13 UML model of our semantic profile

SAWSDL or WSMO-Lite for now) This profile also embedsan internal behaviour description composed of a sequence ofunit activities Each of these unit activities is represented by alist of semantic concepts such as functional descriptionThispart enables description of business or technical sets in orderto facilitate service composition

Using syntactic and semantic information from businessand technical profiles our matchmaking mechanism thencomputes semantic and syntactic distance between modelsIn this view we first perform a ldquo1-to-1rdquo service matchingcomparing semantic concepts and names from both activitiesand web services profiles If no service fits business require-ments of the target activity we then try to respond tothe request using a set of services In order to do so weselect the closest technical service and then deduce a newresearch profile containing uncovered business conceptsThis new profile called complementary profile correspondsto remaining business requirements if we use this first webservice At this time we perform a new service matchingusing this profile and then compute the distance between theproposed sets of services and the initial business activityin order to propose ldquo1-to-119899rdquo matching results to users Thismechanism is performedwith several sets of possible servicesand activities using smart stopping conditions in order tosuggest the best results to user while avoiding combinatorialproblems

Finally service composition results are proposed to userfor validation or selection Figure 20 shows the dedicatedinterface which provides rated results (on the left) for eachactivity or set of activities (on the right)

Once the user has selected technical services we can focuson real data mapping The discovery of web services that fitour functional needs is not enough to generate executableprocesses and ensure good communication between partners

IS We also have to provide interoperability between theseservices

Semantic business information is not sufficient for mes-sage matchmaking One business concept such as a date canbe expressed in many formats (XML date time US dateformat etc)This choice belongs to the service developerwhocan also use classic XML date time declared as such in theservice description or choose to use an exotic one declaredas a simple string In order to solve this problem we proposea technical ontology focused on format concepts and linkedto technical databases filled with syntax representation andconversion formulae

Thanks to semantic and technical data description ofinvolved messages we generate data transformations usingthree main steps for each chosen service

(i) First we search for available outputs using processlogicWe have to find out which previous outputmes-sages can be used to create our input target message

(ii) Then using this available data we try to computethe whole message transformation using semanticlinks between tags format descriptions and technicalinformation about known transformations

(iii) If the whole message is not covered by the computedtransformation we first try to find an available trans-formation service using our service matchmakingmechanism described above We then submit resultsto the user for validation or completion

Once all transformations are validated or completedour concrete level management mechanism generates theexecutable workflow (using BPEL or BPMN 20 languagedepending on targeted execution engine) Links betweenbusiness activities and composed technical services are stored

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

Scientific Programming 7

CIM

PIM

PSM

Businessknowledge

Technicalknowledge

Controlling

2nd cycle

1st cycle

Web serviceworkflow

Figure 5 Relations in collaborative situation life cycle

the collaborative situation life cycle starts with the CIM andmoves from the CIM to the PIM and from the PIM to thePSMThe controlling helps to go back to the CIM and to startover a new cycle But the dimension of collaborative situationlife cycle is not that simple The dimension could be openedand presented in a much more complex way In order topresent the dimensions correctly the relations of collabora-tive life cycle (RCC) are defined (Figure 5)

As presented in the collaborative situation frameworkthe dimension of life cycle is separated as four layers CIMPIM PSM and controllingTheRCC in Figure 3 also containsthese four layers The CIM present or define the gatheredcollaborative knowledge The knowledge of CIM is businessknowledge But the knowledge of PIM is technical knowl-edge In order to move from the CIM to the PIM there isa gap to fix The gap is to add the technical knowledge andtransfer from the CIM to the PIM After gathering technicalknowledge the life cycle moves from the CIM to the PIM

The knowledge of the PIM contains technical functionsof each partner But technical functions are not web servicesThe technical functions have to be implemented or executedby web services Semantic web service is the next gap to fixThen the PIM is transferred to the PSMThe life cycle movesfrom the PIM to the PSMThe PSM is deployed as mediationinformation system (MIS) at runtime (it is an ESB system toorchestrate BPEL file)Though theMIS is launched to invokethe whole collaborative process there may be several kindsof failures and errors at runtimeThis leads to the last layer oflife cycle the controlling The controlling is a layer to decidewhich layers of design-time life cycle should be redone topoint against the specific failures or changes at runtime TheRCC defines two kinds of life cycle

(i) The first life cycle goes back to the PIM layer It isdesigned to solve the failures of technical knowledgeFor example if the web service of one technicalfunction is down the semantic web service has tobe redone to select new web services which couldimplement the technical function

(ii) The second life cycle goes back to the CIM layer Itis designed to correct the mistakes of business knowl-edge For example if a new partner entered thecollaborative situation or a partner is no longer avail-able for the collaborative situation the life cycle has

Strategy level

Operation level

Support level

Feedback infoObjective info

Mean infoFeedback info

Obj

ectiv

e inf

o

Mea

n in

fo

Figure 6 Relations among collaborative situation levels

to restart all over from the beginning to collect thecorrect business information

33 Relations among Levels We have mentioned in previoussection all the models which have been defined in the RCEcover strategy operation and support level There are tworeasons to define these three levels First ISO 9000 [42] hasseparated business process into three types strategy opera-tion and support Second in MISE 10 [44 45] the collabo-rative process only covers operation level With the practicalexperience of research projects operation process is notenough for a collaborative situation which involves decision-making and resource supporting As the results of processdeduction architecture strategy operation and support col-laborative processes are generated But we do not knowwhat are the communications among these processes Howcould strategy process trigger an operation process Howcould a support process complete an operation process Inorder to answer these questions the relations of collaborativelevels (RCL) are defined to manage communications amongdifferent collaborative processes

The communications among strategy level operationlevel and support level have been shown in Figure 6 Among

8 Scientific Programming

these three levels three kinds ofmessages have been involvedobjective information feedback information and mean

(i) Objective information objective is the goal which isintended to attain Objective information is a mes-sage which contains the decision result of strategylevelThe objective information could be sent to oper-ation and support level The operation level and thesupport level invoke homologous process and usefulinformation to attain the goal in objective informa-tion

(ii) Feedback information feedback information is amessage which contains the operation level resultThe feedback information is sent from operation levelto strategy level It is used to report the operationalexception error result and so on Feedback informa-tion could also be sent fromoperation level to supportlevel This kind of feedback information is used totrigger or direct support process

(iii) Mean in the collaboration situation mean is a mes-sage which could contain any kind of information Itcould be an exception an error a feedback or a signal

4 Case Study

The knowledge framework presented in this paper is usedto develop MISE 20 project This project aims to deduceautomatically mediation information system to orchestratethe collaborative process among organizations The method-ology to develop MISE 20 project has been presented in [4647] In this section we will present the use of collaborativeknowledge framework through a small collaborative caseand each step of the case used the methodology presentedin [46 47] but here we are not focusing on the method butthe use result of the framework so the case only shows theresults of CIM PIM and PSMControlling phase is presentedin [48] it is not detailed in this case

41 CIM Organizational Functional and InformationalModel Development [9 47] The knowledge in this phasecovers the target collaborative situation In the work ofDr Rajsiri et al [44] the initial knowledge is structuredaccording to collaborative network partners and commongoal In the work of Dr Truptil et al [49] the sharedfunctions of partners are added to the initial knowledgeThe above two results are combined together and improvedin the methodology The collaborative network model andfunction model represent and define the initial collaborativesituation It covers the CIM organizational functional andinformational knowledge involved strategyoperationsupportlevels

The collaborative network model (Figures 7 and 8) doesnot only collect the collaborative network partners andpartner relations but also collect subcollaborative networkand collaborative objectives The objective of collaborationis classified into three types strategy objective operationobjective and support objective

The function model (Figure 9) is defined based on IDEF1 It represents the information concerning shared partnerfunctions and inputoutput messages

42 PIM ProcessModel Transformation [9 47] In this phasethe collaborative ontology and transformation rules aredefined to transfer the collaboration concepts to the medi-ation concepts in the collaborative ontology meanwhile (i)transfer CIM to PIM and (ii) transfer organizational informa-tional and functional knowledge to process knowledge Thereare five groups of transformation rules create mediatorcreate mediator relationship create generatedmediator func-tion link generatedmediator function tomediator and createintermediator function Table 2 provides two equations ofgroup 1 and group 2 as examples of transformation rules(equations in total 11) With the transformation rules themediation concepts are deduced but there is not enoughknowledge for the extraction of collaborative process so thenext phase comes

The knowledge of this phase presents the matchingbetween objective and functions In this phase one method-ology is developed business service selection to choosefunctions to achieve objectives by linking the functions andobjectives to the instances of the collaborative ontology byusing ldquosame asrdquo and ldquonearbyrdquo relations This part of work isdetailed in [50] Figure 10 shows the interface in mediatormodeling tool which defines the ldquosame asrdquo and ldquonearbyrdquo rela-tions

For the method of process sequence deduction the link-age of inputoutputmessages and the objective basedmethodare mixed to deduce the sequences and the gateways Firstthe linkage of inputoutputmessages among functions is usedto get at global picture of the process Second the specialplace (the gateways are needed) of the global picture is takenand redone by using the objective based method Finallythe linkage of messages checks the results of objective basedmethod to get the best solution

The knowledge covers the collaborative process extrac-tion and sequencegateway deduction In this phase thededuction rules are defined to extract the collaborativeprocess cartography (Figure 11) and collaborative processes(Figure 19) To complete the sequence and the gateway themethod of sequence deduction is developed

43 PSM Technical Process Transformation [22 47] Thefirst task of PSM is to match web services with businessfunctions It covers organizational (web service provider)functional and informational knowledge in PSM with strat-egyoperationsupport levels Whereas a lot of annotationmechanisms exist for web services the recent BPMN 20 isstill devoid of a semantic standard However in addition toa higher design range (from very high level processes to exe-cutable workflows) this secondmajor version brings an XMLrepresentation and its extension mechanism Therefore wedecided to propose our own annotation mechanism calledSA-BPMN 20This extension adds two XML tags (i) Seman-ticDetails allows user to describe any activity requirement Itembeds both functional and internal behaviour description

Scientific Programming 9

Figure 7 Define organizational model

Figure 8 Define organizational model

Each one contains a name and a list ofURIs (corresponding tosemantic concepts fromany ontology) (ii) SemanticElementsaims at describing messages and sequencing flows attach-ing a list of expected messages or elements Each elementthen contains the syntactic name coupled with a list ofconcepts

To simplify semantic annotation the modeling platformembeds annotation tools to allow users to add or edit seman-tic concept references directly from the business processview (see Figure 12) Semantic concepts come from partnersrsquobusiness ontologies developed from scratch or based onMISErsquos one

10 Scientific Programming

Figure 9 Define functional model

Figure 10 Select ldquosame asrdquo and ldquonearbyrdquo instances

Table 2 Examples of transformation rules

Group 1 create mediatorSubnetworkrarrmediator

forallSub Network (X) (forallhasPartner (Sub Network (X) Partner (X1)) and (forallhasPartner (Sub Network (X) Partner (X2))and sdot sdot sdot and

(forallhasPartner (Sub Network (X) Partner (Xn))) (1)997888rarr existMediator (X) andexisthasMediator (Sub Network (X) Mediator (X))

Group 2 create mediator relationshipStrategy and operation objectiverarrmain functionrarr business messagerarr order

If forallStrategy Objective (X1) (forallgenerates (Strategy Objective (X1) Main Function (X1))) and

(2)

forallOperation Objective (X2) (forallgenerates (Operation Objective (X2) Main Function (X2)))If forallMain Function (X1) (forallout (Main Function (X1) Business Message (m))) andforallMain Function (X2) (forallin (Main Function (X2) Business Message (m)))997888rarr exist Order (m) (hasMediatorRelationship (Mediator (X1) Order (m))) andexist Order (m) (hasMediatorRelationship (Mediator (X2) Order (m)))

Scientific Programming 11

Figure 11 Extract process cartography

Figure 12 Semantic annotation of business process (SA-BPMN 20)

Once business processes annotated we aim at matchingbusiness activity semantic descriptions with technical serviceones The proposed approach is based on a ldquo1-to-1rdquo hybridmatchmaking mechanism and focuses on semantic compari-son Semantic distance between profiles is performed thanksto a logic-based reasoning coupled with a syntactic similaritymeasurement These measurements use information from

operation (service capability or activity requirement) andIO In order to perform this service composition anddespite granularity difference of models to match we use asemantic profileThis profile (represented in Figure 13) allowsus to describe the functional aspects of models It is filledwith semantic annotation from business activities (usingour SA-BPMN 20 mechanism) or technical services (using

12 Scientific Programming

Partner

Belongs to

Function

SemanticProfile

SemanticFunction SemanticElement

SemanticPartName stringConcepts ListltURlgt

Input

Output

Required bool

Child

InternalBehavior

UnitFunction

01

01

01

Follows0

lowast

0lowast

0lowast

01

01

01

01

01

01

1lowast

Figure 13 UML model of our semantic profile

SAWSDL or WSMO-Lite for now) This profile also embedsan internal behaviour description composed of a sequence ofunit activities Each of these unit activities is represented by alist of semantic concepts such as functional descriptionThispart enables description of business or technical sets in orderto facilitate service composition

Using syntactic and semantic information from businessand technical profiles our matchmaking mechanism thencomputes semantic and syntactic distance between modelsIn this view we first perform a ldquo1-to-1rdquo service matchingcomparing semantic concepts and names from both activitiesand web services profiles If no service fits business require-ments of the target activity we then try to respond tothe request using a set of services In order to do so weselect the closest technical service and then deduce a newresearch profile containing uncovered business conceptsThis new profile called complementary profile correspondsto remaining business requirements if we use this first webservice At this time we perform a new service matchingusing this profile and then compute the distance between theproposed sets of services and the initial business activityin order to propose ldquo1-to-119899rdquo matching results to users Thismechanism is performedwith several sets of possible servicesand activities using smart stopping conditions in order tosuggest the best results to user while avoiding combinatorialproblems

Finally service composition results are proposed to userfor validation or selection Figure 20 shows the dedicatedinterface which provides rated results (on the left) for eachactivity or set of activities (on the right)

Once the user has selected technical services we can focuson real data mapping The discovery of web services that fitour functional needs is not enough to generate executableprocesses and ensure good communication between partners

IS We also have to provide interoperability between theseservices

Semantic business information is not sufficient for mes-sage matchmaking One business concept such as a date canbe expressed in many formats (XML date time US dateformat etc)This choice belongs to the service developerwhocan also use classic XML date time declared as such in theservice description or choose to use an exotic one declaredas a simple string In order to solve this problem we proposea technical ontology focused on format concepts and linkedto technical databases filled with syntax representation andconversion formulae

Thanks to semantic and technical data description ofinvolved messages we generate data transformations usingthree main steps for each chosen service

(i) First we search for available outputs using processlogicWe have to find out which previous outputmes-sages can be used to create our input target message

(ii) Then using this available data we try to computethe whole message transformation using semanticlinks between tags format descriptions and technicalinformation about known transformations

(iii) If the whole message is not covered by the computedtransformation we first try to find an available trans-formation service using our service matchmakingmechanism described above We then submit resultsto the user for validation or completion

Once all transformations are validated or completedour concrete level management mechanism generates theexecutable workflow (using BPEL or BPMN 20 languagedepending on targeted execution engine) Links betweenbusiness activities and composed technical services are stored

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

8 Scientific Programming

these three levels three kinds ofmessages have been involvedobjective information feedback information and mean

(i) Objective information objective is the goal which isintended to attain Objective information is a mes-sage which contains the decision result of strategylevelThe objective information could be sent to oper-ation and support level The operation level and thesupport level invoke homologous process and usefulinformation to attain the goal in objective informa-tion

(ii) Feedback information feedback information is amessage which contains the operation level resultThe feedback information is sent from operation levelto strategy level It is used to report the operationalexception error result and so on Feedback informa-tion could also be sent fromoperation level to supportlevel This kind of feedback information is used totrigger or direct support process

(iii) Mean in the collaboration situation mean is a mes-sage which could contain any kind of information Itcould be an exception an error a feedback or a signal

4 Case Study

The knowledge framework presented in this paper is usedto develop MISE 20 project This project aims to deduceautomatically mediation information system to orchestratethe collaborative process among organizations The method-ology to develop MISE 20 project has been presented in [4647] In this section we will present the use of collaborativeknowledge framework through a small collaborative caseand each step of the case used the methodology presentedin [46 47] but here we are not focusing on the method butthe use result of the framework so the case only shows theresults of CIM PIM and PSMControlling phase is presentedin [48] it is not detailed in this case

41 CIM Organizational Functional and InformationalModel Development [9 47] The knowledge in this phasecovers the target collaborative situation In the work ofDr Rajsiri et al [44] the initial knowledge is structuredaccording to collaborative network partners and commongoal In the work of Dr Truptil et al [49] the sharedfunctions of partners are added to the initial knowledgeThe above two results are combined together and improvedin the methodology The collaborative network model andfunction model represent and define the initial collaborativesituation It covers the CIM organizational functional andinformational knowledge involved strategyoperationsupportlevels

The collaborative network model (Figures 7 and 8) doesnot only collect the collaborative network partners andpartner relations but also collect subcollaborative networkand collaborative objectives The objective of collaborationis classified into three types strategy objective operationobjective and support objective

The function model (Figure 9) is defined based on IDEF1 It represents the information concerning shared partnerfunctions and inputoutput messages

42 PIM ProcessModel Transformation [9 47] In this phasethe collaborative ontology and transformation rules aredefined to transfer the collaboration concepts to the medi-ation concepts in the collaborative ontology meanwhile (i)transfer CIM to PIM and (ii) transfer organizational informa-tional and functional knowledge to process knowledge Thereare five groups of transformation rules create mediatorcreate mediator relationship create generatedmediator func-tion link generatedmediator function tomediator and createintermediator function Table 2 provides two equations ofgroup 1 and group 2 as examples of transformation rules(equations in total 11) With the transformation rules themediation concepts are deduced but there is not enoughknowledge for the extraction of collaborative process so thenext phase comes

The knowledge of this phase presents the matchingbetween objective and functions In this phase one method-ology is developed business service selection to choosefunctions to achieve objectives by linking the functions andobjectives to the instances of the collaborative ontology byusing ldquosame asrdquo and ldquonearbyrdquo relations This part of work isdetailed in [50] Figure 10 shows the interface in mediatormodeling tool which defines the ldquosame asrdquo and ldquonearbyrdquo rela-tions

For the method of process sequence deduction the link-age of inputoutputmessages and the objective basedmethodare mixed to deduce the sequences and the gateways Firstthe linkage of inputoutputmessages among functions is usedto get at global picture of the process Second the specialplace (the gateways are needed) of the global picture is takenand redone by using the objective based method Finallythe linkage of messages checks the results of objective basedmethod to get the best solution

The knowledge covers the collaborative process extrac-tion and sequencegateway deduction In this phase thededuction rules are defined to extract the collaborativeprocess cartography (Figure 11) and collaborative processes(Figure 19) To complete the sequence and the gateway themethod of sequence deduction is developed

43 PSM Technical Process Transformation [22 47] Thefirst task of PSM is to match web services with businessfunctions It covers organizational (web service provider)functional and informational knowledge in PSM with strat-egyoperationsupport levels Whereas a lot of annotationmechanisms exist for web services the recent BPMN 20 isstill devoid of a semantic standard However in addition toa higher design range (from very high level processes to exe-cutable workflows) this secondmajor version brings an XMLrepresentation and its extension mechanism Therefore wedecided to propose our own annotation mechanism calledSA-BPMN 20This extension adds two XML tags (i) Seman-ticDetails allows user to describe any activity requirement Itembeds both functional and internal behaviour description

Scientific Programming 9

Figure 7 Define organizational model

Figure 8 Define organizational model

Each one contains a name and a list ofURIs (corresponding tosemantic concepts fromany ontology) (ii) SemanticElementsaims at describing messages and sequencing flows attach-ing a list of expected messages or elements Each elementthen contains the syntactic name coupled with a list ofconcepts

To simplify semantic annotation the modeling platformembeds annotation tools to allow users to add or edit seman-tic concept references directly from the business processview (see Figure 12) Semantic concepts come from partnersrsquobusiness ontologies developed from scratch or based onMISErsquos one

10 Scientific Programming

Figure 9 Define functional model

Figure 10 Select ldquosame asrdquo and ldquonearbyrdquo instances

Table 2 Examples of transformation rules

Group 1 create mediatorSubnetworkrarrmediator

forallSub Network (X) (forallhasPartner (Sub Network (X) Partner (X1)) and (forallhasPartner (Sub Network (X) Partner (X2))and sdot sdot sdot and

(forallhasPartner (Sub Network (X) Partner (Xn))) (1)997888rarr existMediator (X) andexisthasMediator (Sub Network (X) Mediator (X))

Group 2 create mediator relationshipStrategy and operation objectiverarrmain functionrarr business messagerarr order

If forallStrategy Objective (X1) (forallgenerates (Strategy Objective (X1) Main Function (X1))) and

(2)

forallOperation Objective (X2) (forallgenerates (Operation Objective (X2) Main Function (X2)))If forallMain Function (X1) (forallout (Main Function (X1) Business Message (m))) andforallMain Function (X2) (forallin (Main Function (X2) Business Message (m)))997888rarr exist Order (m) (hasMediatorRelationship (Mediator (X1) Order (m))) andexist Order (m) (hasMediatorRelationship (Mediator (X2) Order (m)))

Scientific Programming 11

Figure 11 Extract process cartography

Figure 12 Semantic annotation of business process (SA-BPMN 20)

Once business processes annotated we aim at matchingbusiness activity semantic descriptions with technical serviceones The proposed approach is based on a ldquo1-to-1rdquo hybridmatchmaking mechanism and focuses on semantic compari-son Semantic distance between profiles is performed thanksto a logic-based reasoning coupled with a syntactic similaritymeasurement These measurements use information from

operation (service capability or activity requirement) andIO In order to perform this service composition anddespite granularity difference of models to match we use asemantic profileThis profile (represented in Figure 13) allowsus to describe the functional aspects of models It is filledwith semantic annotation from business activities (usingour SA-BPMN 20 mechanism) or technical services (using

12 Scientific Programming

Partner

Belongs to

Function

SemanticProfile

SemanticFunction SemanticElement

SemanticPartName stringConcepts ListltURlgt

Input

Output

Required bool

Child

InternalBehavior

UnitFunction

01

01

01

Follows0

lowast

0lowast

0lowast

01

01

01

01

01

01

1lowast

Figure 13 UML model of our semantic profile

SAWSDL or WSMO-Lite for now) This profile also embedsan internal behaviour description composed of a sequence ofunit activities Each of these unit activities is represented by alist of semantic concepts such as functional descriptionThispart enables description of business or technical sets in orderto facilitate service composition

Using syntactic and semantic information from businessand technical profiles our matchmaking mechanism thencomputes semantic and syntactic distance between modelsIn this view we first perform a ldquo1-to-1rdquo service matchingcomparing semantic concepts and names from both activitiesand web services profiles If no service fits business require-ments of the target activity we then try to respond tothe request using a set of services In order to do so weselect the closest technical service and then deduce a newresearch profile containing uncovered business conceptsThis new profile called complementary profile correspondsto remaining business requirements if we use this first webservice At this time we perform a new service matchingusing this profile and then compute the distance between theproposed sets of services and the initial business activityin order to propose ldquo1-to-119899rdquo matching results to users Thismechanism is performedwith several sets of possible servicesand activities using smart stopping conditions in order tosuggest the best results to user while avoiding combinatorialproblems

Finally service composition results are proposed to userfor validation or selection Figure 20 shows the dedicatedinterface which provides rated results (on the left) for eachactivity or set of activities (on the right)

Once the user has selected technical services we can focuson real data mapping The discovery of web services that fitour functional needs is not enough to generate executableprocesses and ensure good communication between partners

IS We also have to provide interoperability between theseservices

Semantic business information is not sufficient for mes-sage matchmaking One business concept such as a date canbe expressed in many formats (XML date time US dateformat etc)This choice belongs to the service developerwhocan also use classic XML date time declared as such in theservice description or choose to use an exotic one declaredas a simple string In order to solve this problem we proposea technical ontology focused on format concepts and linkedto technical databases filled with syntax representation andconversion formulae

Thanks to semantic and technical data description ofinvolved messages we generate data transformations usingthree main steps for each chosen service

(i) First we search for available outputs using processlogicWe have to find out which previous outputmes-sages can be used to create our input target message

(ii) Then using this available data we try to computethe whole message transformation using semanticlinks between tags format descriptions and technicalinformation about known transformations

(iii) If the whole message is not covered by the computedtransformation we first try to find an available trans-formation service using our service matchmakingmechanism described above We then submit resultsto the user for validation or completion

Once all transformations are validated or completedour concrete level management mechanism generates theexecutable workflow (using BPEL or BPMN 20 languagedepending on targeted execution engine) Links betweenbusiness activities and composed technical services are stored

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

Scientific Programming 9

Figure 7 Define organizational model

Figure 8 Define organizational model

Each one contains a name and a list ofURIs (corresponding tosemantic concepts fromany ontology) (ii) SemanticElementsaims at describing messages and sequencing flows attach-ing a list of expected messages or elements Each elementthen contains the syntactic name coupled with a list ofconcepts

To simplify semantic annotation the modeling platformembeds annotation tools to allow users to add or edit seman-tic concept references directly from the business processview (see Figure 12) Semantic concepts come from partnersrsquobusiness ontologies developed from scratch or based onMISErsquos one

10 Scientific Programming

Figure 9 Define functional model

Figure 10 Select ldquosame asrdquo and ldquonearbyrdquo instances

Table 2 Examples of transformation rules

Group 1 create mediatorSubnetworkrarrmediator

forallSub Network (X) (forallhasPartner (Sub Network (X) Partner (X1)) and (forallhasPartner (Sub Network (X) Partner (X2))and sdot sdot sdot and

(forallhasPartner (Sub Network (X) Partner (Xn))) (1)997888rarr existMediator (X) andexisthasMediator (Sub Network (X) Mediator (X))

Group 2 create mediator relationshipStrategy and operation objectiverarrmain functionrarr business messagerarr order

If forallStrategy Objective (X1) (forallgenerates (Strategy Objective (X1) Main Function (X1))) and

(2)

forallOperation Objective (X2) (forallgenerates (Operation Objective (X2) Main Function (X2)))If forallMain Function (X1) (forallout (Main Function (X1) Business Message (m))) andforallMain Function (X2) (forallin (Main Function (X2) Business Message (m)))997888rarr exist Order (m) (hasMediatorRelationship (Mediator (X1) Order (m))) andexist Order (m) (hasMediatorRelationship (Mediator (X2) Order (m)))

Scientific Programming 11

Figure 11 Extract process cartography

Figure 12 Semantic annotation of business process (SA-BPMN 20)

Once business processes annotated we aim at matchingbusiness activity semantic descriptions with technical serviceones The proposed approach is based on a ldquo1-to-1rdquo hybridmatchmaking mechanism and focuses on semantic compari-son Semantic distance between profiles is performed thanksto a logic-based reasoning coupled with a syntactic similaritymeasurement These measurements use information from

operation (service capability or activity requirement) andIO In order to perform this service composition anddespite granularity difference of models to match we use asemantic profileThis profile (represented in Figure 13) allowsus to describe the functional aspects of models It is filledwith semantic annotation from business activities (usingour SA-BPMN 20 mechanism) or technical services (using

12 Scientific Programming

Partner

Belongs to

Function

SemanticProfile

SemanticFunction SemanticElement

SemanticPartName stringConcepts ListltURlgt

Input

Output

Required bool

Child

InternalBehavior

UnitFunction

01

01

01

Follows0

lowast

0lowast

0lowast

01

01

01

01

01

01

1lowast

Figure 13 UML model of our semantic profile

SAWSDL or WSMO-Lite for now) This profile also embedsan internal behaviour description composed of a sequence ofunit activities Each of these unit activities is represented by alist of semantic concepts such as functional descriptionThispart enables description of business or technical sets in orderto facilitate service composition

Using syntactic and semantic information from businessand technical profiles our matchmaking mechanism thencomputes semantic and syntactic distance between modelsIn this view we first perform a ldquo1-to-1rdquo service matchingcomparing semantic concepts and names from both activitiesand web services profiles If no service fits business require-ments of the target activity we then try to respond tothe request using a set of services In order to do so weselect the closest technical service and then deduce a newresearch profile containing uncovered business conceptsThis new profile called complementary profile correspondsto remaining business requirements if we use this first webservice At this time we perform a new service matchingusing this profile and then compute the distance between theproposed sets of services and the initial business activityin order to propose ldquo1-to-119899rdquo matching results to users Thismechanism is performedwith several sets of possible servicesand activities using smart stopping conditions in order tosuggest the best results to user while avoiding combinatorialproblems

Finally service composition results are proposed to userfor validation or selection Figure 20 shows the dedicatedinterface which provides rated results (on the left) for eachactivity or set of activities (on the right)

Once the user has selected technical services we can focuson real data mapping The discovery of web services that fitour functional needs is not enough to generate executableprocesses and ensure good communication between partners

IS We also have to provide interoperability between theseservices

Semantic business information is not sufficient for mes-sage matchmaking One business concept such as a date canbe expressed in many formats (XML date time US dateformat etc)This choice belongs to the service developerwhocan also use classic XML date time declared as such in theservice description or choose to use an exotic one declaredas a simple string In order to solve this problem we proposea technical ontology focused on format concepts and linkedto technical databases filled with syntax representation andconversion formulae

Thanks to semantic and technical data description ofinvolved messages we generate data transformations usingthree main steps for each chosen service

(i) First we search for available outputs using processlogicWe have to find out which previous outputmes-sages can be used to create our input target message

(ii) Then using this available data we try to computethe whole message transformation using semanticlinks between tags format descriptions and technicalinformation about known transformations

(iii) If the whole message is not covered by the computedtransformation we first try to find an available trans-formation service using our service matchmakingmechanism described above We then submit resultsto the user for validation or completion

Once all transformations are validated or completedour concrete level management mechanism generates theexecutable workflow (using BPEL or BPMN 20 languagedepending on targeted execution engine) Links betweenbusiness activities and composed technical services are stored

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

10 Scientific Programming

Figure 9 Define functional model

Figure 10 Select ldquosame asrdquo and ldquonearbyrdquo instances

Table 2 Examples of transformation rules

Group 1 create mediatorSubnetworkrarrmediator

forallSub Network (X) (forallhasPartner (Sub Network (X) Partner (X1)) and (forallhasPartner (Sub Network (X) Partner (X2))and sdot sdot sdot and

(forallhasPartner (Sub Network (X) Partner (Xn))) (1)997888rarr existMediator (X) andexisthasMediator (Sub Network (X) Mediator (X))

Group 2 create mediator relationshipStrategy and operation objectiverarrmain functionrarr business messagerarr order

If forallStrategy Objective (X1) (forallgenerates (Strategy Objective (X1) Main Function (X1))) and

(2)

forallOperation Objective (X2) (forallgenerates (Operation Objective (X2) Main Function (X2)))If forallMain Function (X1) (forallout (Main Function (X1) Business Message (m))) andforallMain Function (X2) (forallin (Main Function (X2) Business Message (m)))997888rarr exist Order (m) (hasMediatorRelationship (Mediator (X1) Order (m))) andexist Order (m) (hasMediatorRelationship (Mediator (X2) Order (m)))

Scientific Programming 11

Figure 11 Extract process cartography

Figure 12 Semantic annotation of business process (SA-BPMN 20)

Once business processes annotated we aim at matchingbusiness activity semantic descriptions with technical serviceones The proposed approach is based on a ldquo1-to-1rdquo hybridmatchmaking mechanism and focuses on semantic compari-son Semantic distance between profiles is performed thanksto a logic-based reasoning coupled with a syntactic similaritymeasurement These measurements use information from

operation (service capability or activity requirement) andIO In order to perform this service composition anddespite granularity difference of models to match we use asemantic profileThis profile (represented in Figure 13) allowsus to describe the functional aspects of models It is filledwith semantic annotation from business activities (usingour SA-BPMN 20 mechanism) or technical services (using

12 Scientific Programming

Partner

Belongs to

Function

SemanticProfile

SemanticFunction SemanticElement

SemanticPartName stringConcepts ListltURlgt

Input

Output

Required bool

Child

InternalBehavior

UnitFunction

01

01

01

Follows0

lowast

0lowast

0lowast

01

01

01

01

01

01

1lowast

Figure 13 UML model of our semantic profile

SAWSDL or WSMO-Lite for now) This profile also embedsan internal behaviour description composed of a sequence ofunit activities Each of these unit activities is represented by alist of semantic concepts such as functional descriptionThispart enables description of business or technical sets in orderto facilitate service composition

Using syntactic and semantic information from businessand technical profiles our matchmaking mechanism thencomputes semantic and syntactic distance between modelsIn this view we first perform a ldquo1-to-1rdquo service matchingcomparing semantic concepts and names from both activitiesand web services profiles If no service fits business require-ments of the target activity we then try to respond tothe request using a set of services In order to do so weselect the closest technical service and then deduce a newresearch profile containing uncovered business conceptsThis new profile called complementary profile correspondsto remaining business requirements if we use this first webservice At this time we perform a new service matchingusing this profile and then compute the distance between theproposed sets of services and the initial business activityin order to propose ldquo1-to-119899rdquo matching results to users Thismechanism is performedwith several sets of possible servicesand activities using smart stopping conditions in order tosuggest the best results to user while avoiding combinatorialproblems

Finally service composition results are proposed to userfor validation or selection Figure 20 shows the dedicatedinterface which provides rated results (on the left) for eachactivity or set of activities (on the right)

Once the user has selected technical services we can focuson real data mapping The discovery of web services that fitour functional needs is not enough to generate executableprocesses and ensure good communication between partners

IS We also have to provide interoperability between theseservices

Semantic business information is not sufficient for mes-sage matchmaking One business concept such as a date canbe expressed in many formats (XML date time US dateformat etc)This choice belongs to the service developerwhocan also use classic XML date time declared as such in theservice description or choose to use an exotic one declaredas a simple string In order to solve this problem we proposea technical ontology focused on format concepts and linkedto technical databases filled with syntax representation andconversion formulae

Thanks to semantic and technical data description ofinvolved messages we generate data transformations usingthree main steps for each chosen service

(i) First we search for available outputs using processlogicWe have to find out which previous outputmes-sages can be used to create our input target message

(ii) Then using this available data we try to computethe whole message transformation using semanticlinks between tags format descriptions and technicalinformation about known transformations

(iii) If the whole message is not covered by the computedtransformation we first try to find an available trans-formation service using our service matchmakingmechanism described above We then submit resultsto the user for validation or completion

Once all transformations are validated or completedour concrete level management mechanism generates theexecutable workflow (using BPEL or BPMN 20 languagedepending on targeted execution engine) Links betweenbusiness activities and composed technical services are stored

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

Scientific Programming 11

Figure 11 Extract process cartography

Figure 12 Semantic annotation of business process (SA-BPMN 20)

Once business processes annotated we aim at matchingbusiness activity semantic descriptions with technical serviceones The proposed approach is based on a ldquo1-to-1rdquo hybridmatchmaking mechanism and focuses on semantic compari-son Semantic distance between profiles is performed thanksto a logic-based reasoning coupled with a syntactic similaritymeasurement These measurements use information from

operation (service capability or activity requirement) andIO In order to perform this service composition anddespite granularity difference of models to match we use asemantic profileThis profile (represented in Figure 13) allowsus to describe the functional aspects of models It is filledwith semantic annotation from business activities (usingour SA-BPMN 20 mechanism) or technical services (using

12 Scientific Programming

Partner

Belongs to

Function

SemanticProfile

SemanticFunction SemanticElement

SemanticPartName stringConcepts ListltURlgt

Input

Output

Required bool

Child

InternalBehavior

UnitFunction

01

01

01

Follows0

lowast

0lowast

0lowast

01

01

01

01

01

01

1lowast

Figure 13 UML model of our semantic profile

SAWSDL or WSMO-Lite for now) This profile also embedsan internal behaviour description composed of a sequence ofunit activities Each of these unit activities is represented by alist of semantic concepts such as functional descriptionThispart enables description of business or technical sets in orderto facilitate service composition

Using syntactic and semantic information from businessand technical profiles our matchmaking mechanism thencomputes semantic and syntactic distance between modelsIn this view we first perform a ldquo1-to-1rdquo service matchingcomparing semantic concepts and names from both activitiesand web services profiles If no service fits business require-ments of the target activity we then try to respond tothe request using a set of services In order to do so weselect the closest technical service and then deduce a newresearch profile containing uncovered business conceptsThis new profile called complementary profile correspondsto remaining business requirements if we use this first webservice At this time we perform a new service matchingusing this profile and then compute the distance between theproposed sets of services and the initial business activityin order to propose ldquo1-to-119899rdquo matching results to users Thismechanism is performedwith several sets of possible servicesand activities using smart stopping conditions in order tosuggest the best results to user while avoiding combinatorialproblems

Finally service composition results are proposed to userfor validation or selection Figure 20 shows the dedicatedinterface which provides rated results (on the left) for eachactivity or set of activities (on the right)

Once the user has selected technical services we can focuson real data mapping The discovery of web services that fitour functional needs is not enough to generate executableprocesses and ensure good communication between partners

IS We also have to provide interoperability between theseservices

Semantic business information is not sufficient for mes-sage matchmaking One business concept such as a date canbe expressed in many formats (XML date time US dateformat etc)This choice belongs to the service developerwhocan also use classic XML date time declared as such in theservice description or choose to use an exotic one declaredas a simple string In order to solve this problem we proposea technical ontology focused on format concepts and linkedto technical databases filled with syntax representation andconversion formulae

Thanks to semantic and technical data description ofinvolved messages we generate data transformations usingthree main steps for each chosen service

(i) First we search for available outputs using processlogicWe have to find out which previous outputmes-sages can be used to create our input target message

(ii) Then using this available data we try to computethe whole message transformation using semanticlinks between tags format descriptions and technicalinformation about known transformations

(iii) If the whole message is not covered by the computedtransformation we first try to find an available trans-formation service using our service matchmakingmechanism described above We then submit resultsto the user for validation or completion

Once all transformations are validated or completedour concrete level management mechanism generates theexecutable workflow (using BPEL or BPMN 20 languagedepending on targeted execution engine) Links betweenbusiness activities and composed technical services are stored

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

12 Scientific Programming

Partner

Belongs to

Function

SemanticProfile

SemanticFunction SemanticElement

SemanticPartName stringConcepts ListltURlgt

Input

Output

Required bool

Child

InternalBehavior

UnitFunction

01

01

01

Follows0

lowast

0lowast

0lowast

01

01

01

01

01

01

1lowast

Figure 13 UML model of our semantic profile

SAWSDL or WSMO-Lite for now) This profile also embedsan internal behaviour description composed of a sequence ofunit activities Each of these unit activities is represented by alist of semantic concepts such as functional descriptionThispart enables description of business or technical sets in orderto facilitate service composition

Using syntactic and semantic information from businessand technical profiles our matchmaking mechanism thencomputes semantic and syntactic distance between modelsIn this view we first perform a ldquo1-to-1rdquo service matchingcomparing semantic concepts and names from both activitiesand web services profiles If no service fits business require-ments of the target activity we then try to respond tothe request using a set of services In order to do so weselect the closest technical service and then deduce a newresearch profile containing uncovered business conceptsThis new profile called complementary profile correspondsto remaining business requirements if we use this first webservice At this time we perform a new service matchingusing this profile and then compute the distance between theproposed sets of services and the initial business activityin order to propose ldquo1-to-119899rdquo matching results to users Thismechanism is performedwith several sets of possible servicesand activities using smart stopping conditions in order tosuggest the best results to user while avoiding combinatorialproblems

Finally service composition results are proposed to userfor validation or selection Figure 20 shows the dedicatedinterface which provides rated results (on the left) for eachactivity or set of activities (on the right)

Once the user has selected technical services we can focuson real data mapping The discovery of web services that fitour functional needs is not enough to generate executableprocesses and ensure good communication between partners

IS We also have to provide interoperability between theseservices

Semantic business information is not sufficient for mes-sage matchmaking One business concept such as a date canbe expressed in many formats (XML date time US dateformat etc)This choice belongs to the service developerwhocan also use classic XML date time declared as such in theservice description or choose to use an exotic one declaredas a simple string In order to solve this problem we proposea technical ontology focused on format concepts and linkedto technical databases filled with syntax representation andconversion formulae

Thanks to semantic and technical data description ofinvolved messages we generate data transformations usingthree main steps for each chosen service

(i) First we search for available outputs using processlogicWe have to find out which previous outputmes-sages can be used to create our input target message

(ii) Then using this available data we try to computethe whole message transformation using semanticlinks between tags format descriptions and technicalinformation about known transformations

(iii) If the whole message is not covered by the computedtransformation we first try to find an available trans-formation service using our service matchmakingmechanism described above We then submit resultsto the user for validation or completion

Once all transformations are validated or completedour concrete level management mechanism generates theexecutable workflow (using BPEL or BPMN 20 languagedepending on targeted execution engine) Links betweenbusiness activities and composed technical services are stored

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

Scientific Programming 13

0

5

10

15

20

25

30

35

Func

tions

4 6 8 102Partners

Normal caseSimple caseComplex case

Figure 14 Number of functions in different cases [9]

in order to enable business monitoring during the runtimephase (see Figure 21) It covers process knowledge in PSM withstrategyoperationsupport levels

5 Evaluation

51 Part One Evaluation of Collaborative Framework Threecases were built to calculate the number of functions (CIM)[9] sequence flows (PIM) [9] and web services (PSM)The performance of collaborative knowledge framework ineach life cycle can be evaluated ldquoNormal caserdquo means thatthe collaborative process goes from one partner to anotherpartner with MISE The ldquosimple caserdquo means that there is amediator but only mathematic calculation For example onepartner function is invoked by onemediator function and thenumber of partner functions and mediator functions shouldbe equal If we consider only the mathematics the number oftotal functions is simply doubled The ldquocomplex caserdquo is thereal result of MISE with collaborative framework presentedin this paper

As shown in Figure 14 for the ldquocomplex caserdquo bythe increase in partners the number of functions can bedecreased and is infinitely close to the ldquono mediatorrdquo caseIn Figure 15 the ldquomediatorrdquo combines the same functionsof partners into one invoking function For the simple casemore partners lead to more sequence flows For the complexcase with the invoking function more partners lead to moresequence flows being saved With the merging and invok-ing functions the complexity of the collaborative processdecreases Figure 16 shows the numbers of web services inthree cases As the complexity is increasing the number ofweb services in MISE is much less than the one in simplecase The MISE methodology with collaborative knowledgeframework shows the strong advantage of addressing a complexcollaborative situation

Except the evaluation of each step we also did anevaluation between MISE 10 and MSIE 20 During theresearch of MSIE 10 the collaborative knowledge network

4 6 8 102Partners

Normal caseSimple caseComplex case

0

5

10

15

20

25

30

35

40

45

50

Sequ

ence

flow

s

Figure 15 Number of sequences in different cases [9]

4 6 8 102Partners

Normal caseSimple caseComplex case

0

10

20

30

40

50

60

Web

serv

ices

Figure 16 Number of web services in different cases

was not yet developed All the research work is dependingon theMDA and SOA theory With the complement of MISE10 many problems appear So in the research of MISE 20the collaborative knowledge framework is developed firstto avoid the mistakes in MISE 10 and to conclude newconsiderations agility and automation Figure 22 shows theevaluation results

(i) Cause of the addition of controlling MISE 20 hasstrong agility

(ii) Cause of the addition of knowledge gathering processand knowledge classificationMSIE 20 gatheredmorecomplete knowledge in organization function pro-cess and data

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

14 Scientific Programming

CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[9]

[9]

[9]

[22]

[22] [22]

[48]7

5 6

3

2

4

1

Figure 17 The developing path of MISE 20 methodology

(iii) Cause of the collaborative levels even though bothhave the same level of interoperability MISE 20 hasclearer process levels and process cartography

52 Part Two Comparisons of Related Works The collabora-tive knowledge framework defines the knowledge that shouldbe gathered or covered during the collaboration Section 6has introduced the MISE 20 developing methodology thismethodology is based on the framework and follows theknowledge gathering steps which are defined in the frame-work In order to evaluate the framework the MISE 20 caseis located in Figure 17

Several problems have been found

(i) Once strategyoperationsupport objectives and func-tions have been collected in CIM the strategyopera-tionsupport knowledge in PIM and PSM can beskipped

(ii) Once organizationfunctionalinformational knowl-edge has been collected in CIM the process knowl-edge of CIM can be skipped The transformationdirectly to the process knowledge in PIM is moreuseful

(iii) In PSM the informational and functional knowledgeis more important for the transformation of processin PSM and the organizational information can beskipped

In order to evaluate the collaborative knowledge frame-work we searched papers published from 2015 to 2017 inWeb of Science using key words ldquocollaborative knowledgerdquoand ldquoframeworkrdquo 338 papers have been found After manual

selection we got 13 papers which are strongly related tothis paper Those 12 papers are summarized in Table 3 andFigure 18 [18 20] are review papers The paper [18] reviewedall the enterprise architectures from life cycle and modelingviews Compared with the collaborative knowledge frame-work the modeling views are similar with regard to orga-nizational informational functional and process elements(collaborative situation elements) But the life cycles are verydifferent depending on the purpose of framework All those13 papers can be located into strategyoperationsupportlevels (Figure 5) For controlling there are no papers locatedBut another word for controlling could be agility [48] givesa careful review according to agility So this step is skipped inthis paper

We conclude the following

(i) The collaborative knowledge framework did give aguide to gather knowledge and deduce automaticallythe collaborative process and workflow

(ii) The final purpose of collaborative knowledge frame-work is to develop aMIS based onMDA the life cycleis different from others

(iii) The same knowledge gathering has been repeatedin the framework our suggestion is to gather orga-nizationalinformationfunctional in CIM deduceprocess in PIM carefully gather informationalfunc-tional in PSM and deduce workflow in PMS

(iv) For controlling depending on different event theknowledge should be adapted back to differencelevels

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

Scientific Programming 15

[16][13]CIM

PIM

PSM

Controlling

Organizational Informational Functional Process

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

Strategy

Operation

Support

[10][12]

[11][17] [14]

[15]

[19]

[20]

[21]

[20]

[18]

[18]

Figure 18 The positions of related papers

Figure 19 Extract collaborative processes

Figure 20 Service matchmaking validation by user

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

16 Scientific Programming

Table 3 Summary of collaborative knowledge works

Ref Publishedyear

Frameworkknowledge modeled Method

[10] 2016 Collaborative network on operation Questionnaire[11] 2017 Web services Semantic annotation[12] 2017 Collaborative network on operation Matrix for collaborative innovation[13] 2017 Collaborative network and objectives on operation Interview and case study[14] 2016 Process in PSM Knowledge based software developing[15] 2016 Collaborative network on resources ABC framework and case study

[16] 2016 Collaborative agencies and process on operation(material time info) Knowledge framework for collaborative simulation

[17] 2016 Web services Service ontology[18] 2016 Life cycle and modeling views Review[19] 2016 Web services and process on strategy Ontology learning[20] 2016 Actor and behavior on CIM Review[21] 2015 Partners and process on operation Case study

createCADFile datatransf

datatransf

datatransf

datatransf

datatransf

Prepareproduction

Prepareproduction

Developproduct design

plan

Design andbuild prototype Test prototype

testPrototype

fixDesignModel

chooseMaterials

producePart++

Figure 21 Comparison between business process and generated workflow

6 Conclusion

MISE 20 aims to develop a mediation information systemwhich manages process orchestration data conversion andservice selection in enterprisesrsquo information systems To doso the first problem is to define or deduce a business collab-orative process This paper presents abstract framework fordeducing business collaborative process model In relationsof elements organizational model collaborative networkmodel IDEF0 based functional model IDEF1 informationalmodel and BPMN based collaborative process model areused to present collaborative knowledge Metamodel isdefined to confirm each model Relations of life cycle definethe agility management in the MISE 20 In relations amonglevels we defined types of messages transferred amongstrategy operation and support process

With the accomplishment of models metamodel andtransformation rules software tool is going to develop to

support modelsrsquo building and transformation rulesrsquo imple-mentation The MISE 20 abstract level software tool shouldimplement the following three main functions (i) creationof organizational model functional model informationalmodel and process model (use GWT and Java 2D graphi-cal design) (ii) transformation from organizational modelfunctional model and informational model to process model(use JDOM Java or ATL) (iii) extraction of the BPMNcollaborative process cartography (use JDOM and Java) Thedetailed explanation of deduction of collaborative processcartography is presented in [51]

The whole BPMN collaborative process cartography isprovided to MISE 20 concrete level Concrete level concernsMIS deployment Firstly with provided process cartographyin abstract level web services are selected automaticallyby semantic annotation and semantic ontology And thenbusiness process cartography is transferred into executabletechnical process The BPMN based collaborative process

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

Scientific Programming 17

Interoperability Agility Life cycle Organizationalknowledge

Functionalknowledge

Processknowledge

Dataknowledge

MISE 10 5 0 3 3 5 3 4MISE 20 5 5 4 5 5 5 5

5

0

3 3

5

34

5 54

5 5 5 5

0123456

Figure 22 The developing path of MISE 20 methodology

cartography is transferred to BPEL [52] file and deployedin ESB (Enterprise Service Bus) The concrete level work ispresented in [53]

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This work was supported by ARMINES (Acteur de lrsquoInnova-tion par la Recherche Partenariale) in France and NationalHigher-Education Institution General Research and Devel-opment Funding of China (B15JB00340)

References

[1] D Chen G Doumeingts and F Vernadat ldquoArchitectures forenterprise integration and interoperability past present andfuturerdquo Computers in Industry vol 59 no 7 pp 647ndash659 2008

[2] C Nicolle J C Simon and K Yetongnon ldquoInteroperability ofinformation systemsrdquo Database vol 1651 p 1650 2005

[3] D S Milojicic V Kalogeraki R Lukose et al ldquoPeer-to-peercomputingrdquo Citeseer 2002

[4] N Guarino and P Giaretta ldquoOntologies and knowledgebasesmdashtowards a terminological clarificationrdquo in Towards VeryLarge Knowledge Bases pp 25ndash32 IOS Press Amsterdam TheNetherlands 1995

[5] G Wiederhold ldquoMediators in the architecture of future infor-mation systemsrdquo Computer vol 25 no 3 pp 38ndash49 1992

[6] J Bezivin S Gerard P A Muller and L Rioux MDA Compo-nents Challenges and Opportunities 2003

[7] N Josuttis SOA in Practice Orsquoreilly 2007[8] J Miller and J Mukerji ldquoMDA Guide Version 10 1rdquo Object

Management Group vol 234 p 51 2003[9] W Mu F Benaben and H Pingaud ldquoA methodology proposal

for collaborative business process elaboration using a model-driven approachrdquo Enterprise Information Systems vol 9 no 4pp 349ndash383 2015

[10] S Oppl ldquoSupporting the Collaborative Construction of aShared Understanding About Work with a Guided ConceptualModeling Techniquerdquo Group Decision and Negotiation vol 26no 2 pp 247ndash283 2017

[11] G Guerrero-Contreras J L Navarro-Galindo J Samos andJ L Garrido ldquoA collaborative semantic annotation system inhealth towards a SOADesign for knowledge sharing in ambient

intelligencerdquo Mobile Information Systems vol 2017 Article ID4759572 10 pages 2017

[12] B Knoke M Missikoff and K-DThoben ldquoCollaborative openinnovation management in virtual manufacturing enterprisesrdquoInternational Journal of Computer Integrated Manufacturingvol 30 no 1 pp 158ndash166 2017

[13] W Medema J Adamowski C Orr A Furber A Wals andN Milot ldquoBuilding a foundation for knowledge co-creation incollaborative water governance Dimensions of stakeholder net-works facilitated through bridging organizationsrdquoWater vol 9no 1 article no 60 2017

[14] M Milosevic D Lukic A Antic B Lalic M Ficko and GSimunovic ldquoe-CAPP A distributed collaborative system forinternet-based process planningrdquo Journal of ManufacturingSystems vol 42 pp 210ndash223 2017

[15] E Yeboah-Assiamah K Muller and K A Domfeh ldquoRising tothe challenge a framework for optimising value in collaborativenatural resource governancerdquo Forest Policy and Economics vol67 pp 20ndash29 2016

[16] Q Long ldquoA multi-methodological collaborative simulation forinter-organizational supply chain networksrdquo Knowledge-BasedSystems vol 96 pp 84ndash95 2016

[17] S Y Xu and B Raahemi ldquoA semantic-based service discoveryframework for collaborative environmentsrdquo International Jour-nal of Simulation Modelling vol 15 no 1 pp 83ndash96 2016

[18] A Vargas L Cuenca A Boza I Sacala and M MoisesculdquoTowards the development of the framework for inter sensingenterprise architecturerdquo Journal of Intelligent Manufacturingvol 27 no 1 pp 55ndash72 2016

[19] R Costa C Lima J Sarraipa and R Jardim-Goncalves ldquoFacili-tating knowledge sharing and reuse in building and construc-tion domain an ontology-based approachrdquo Journal of IntelligentManufacturing vol 27 no 1 pp 263ndash282 2016

[20] C Durugbo ldquoCollaborative networks A systematic reviewandmulti-level frameworkrdquo International Journal of ProductionResearch vol 54 no 12 pp 3749ndash3776 2016

[21] K Shahriari A G Hessami A Jadidi and N Lehoux ldquoAnapproach toward a conceptual collaborative framework basedon a case study in a wood supply chainrdquo IEEE Systems Journalvol 9 no 4 pp 1163ndash1172 2015

[22] N Boissel-Dallier F Benaben J-P Lorre and H PingaudldquoMediation information system engineering based on hybridservice composition mechanismrdquo Journal of Systems and Soft-ware vol 108 pp 39ndash59 2015

[23] D A Chappell Enterprise Service Bus OrsquoReilly Media 2004[24] A-M Barthe-Delanoe S Carbonnel F Benaben and H Pin-

gaud ldquoEvent-driven agility of crisis management collaborative

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

18 Scientific Programming

processesrdquo in Proceedings of the 9th International Conferenceon Information Systems for Crisis Response and Management(ISCRAM rsquo12) Vancouver Canada April 2012

[25] L M Camarinha-Matos and H Afsarmanesh ldquoOn referencemodels for collaborative networked organizationsrdquo Interna-tional Journal of Production Research vol 46 no 9 pp 2453ndash2469 2008

[26] J A Zachman ldquoA framework for information systems architec-turerdquo IBM Systems Journal vol 26 no 3 pp 276ndash292 1987

[27] DTIC Technical Architecture Framework for Information Man-agement Volumes 1ndash8 Version 30 (Computer Diskette) 1996

[28] N Umheh A Miller and C Dagli TOGAF vs DoDAF Archi-tecting Frameworks for Net-Centric Systems 2007

[29] C4ISR C4ISR Architecture Framework Version 20 AWGmdashUSDepartment of Defence 1997

[30] B Biggs ldquoMinistry of Defence Architectural Framework(MODAF)rdquo IEE Seminar on UML Systems Engineering vol2005 no 10814 pp 43ndash82 2005

[31] J Zachman The Zachman Framework for Enterprise Architec-ture Zachman International 2002

[32] D Chen B Vallespir and G Doumeingts ldquoGRAI integratedmethodology and its mapping onto generic enterprise referencearchitecture and methodologyrdquo Computers in Industry vol 33no 2-3 pp 387ndash394 1997

[33] G Doumeingts B Vallespir and D Chen ldquoGRAI GridDeci-sional modellingrdquo in Handbook on Architectures of InformationSystems pp 321ndash346 2006

[34] T J Williams and H Li ldquoPERA and GERAMmdashenterprisereference architectures in enterprise integrationrdquo in InformationInfrastructure Systems for Manufacturing II pp 3ndash30 1999

[35] A W Scheer ARIS-Business Process Modeling Springer 2000[36] K Kosanke ldquoCIMOSA - Overview and statusrdquo Computers in

Industry vol 27 no 2 pp 101ndash109 1995[37] J Vamus and N Panaich TOGAF 9 Survey Results Presentation

2009[38] I I Force ldquoGERAM Generalised Enterprise Reference Archi-

tecture and Methodologyrdquo IFIP-IFAC Task Force ArchitEnterp Integr Tech Rep 1999

[39] C I O Council Federal Enterprise Architecture Framework(FEAF)mdashVersion 11 1999

[40] IDEAS A Gap AnalysismdashRequired Activities in Research Tech-nology and Standardisation to Close The RTS GapmdashRoadmapsAnd Recommendations on RTS Activites 2003

[41] A Berre et al ldquoThe ATHENA interoperability frameworkrdquo inEnterprise Interoperability II pp 569ndash580 2007

[42] ISO 9000 ldquoISO 9000 Quality managementrdquo September 2005httpwwwisoorgisohomestorepublications and e-productspublication itemhtmpid=PUB100224

[43] ISO 9000 X50-130 ldquoNF EN ISO 9000 X50-130 Systemes demanagement de la qualitemdashPrincipes essentiels et vocabu-lairerdquo October 2005 httpcatdocmines-albifr8080Recordhtmidlist=6amprecord=19143202124919614849

[44] V Rajsiri J-P Lorre F Benaben and H Pingaud ldquoKnowledge-based system for collaborative process specificationrdquoComputersin Industry vol 61 no 2 pp 161ndash175 2010

[45] J Touzi F Benaben H Pingaud and J P Lorre ldquoA model-driven approach for collaborative service-oriented architecturedesignrdquo International Journal of Production Economics vol 121no 1 pp 5ndash20 2009

[46] F Benaben and F B Vernadat ldquoInformation System agilityto support collaborative organisationsrdquo Enterprise InformationSystems vol 11 no 4 pp 470ndash473 2017

[47] F Benaben W Mu N Boissel-Dallier A-M Barthe-DelanoeS Zribi andH Pingaud ldquoSupporting interoperability of collab-orative networks through engineering of a service-based Medi-ation Information System (MISE 20)rdquo Enterprise InformationSystems vol 9 pp 556ndash582 2015

[48] A-M Barthe-Delanoe S Truptil F Benaben and H PingaudldquoEvent-driven agility of interoperability during the Run-time ofcollaborative processesrdquoDecision Support Systems vol 59 no 1pp 171ndash179 2014

[49] S Truptil F Benaben H Pingaud and C Hanachi ldquoUne archi-tecture de systeme drsquoinformation collaboratif pour la gestionde criserdquo in Proceedings of the INFORSID09 2009

[50] W Mu F Benaben and H Pingaud ldquoAn ontology basedcollaborative business service selectionmdashcontributing to auto-matic building of collaborative business processrdquo in Risks andResilience of Collaborative Networks L M CamarinhaMatos FBenaben and W Picard Eds vol 463 pp 639ndash651 SpringerBerlin Germany 2015

[51] W Mu Caracterisation et logique drsquoune situation collaborativeINPT Toulouse France 2012

[52] S Lee T-Y Kim D Kang K Kim and J Y Lee ldquoCompositionof executable business process models by combining businessrules and process flowsrdquo Expert Systems with Applications vol33 no 1 pp 221ndash229 2007

[53] F Benaben N Boissel-Dallier J-P Lorre and H Pin-gaud ldquoSemantic reconciliation in interoperability managementthroughmodel-driven approachrdquo IFIP Advances in Informationand Communication Technology vol 336 pp 705ndash712 2010

Submit your manuscripts athttpswwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Distributed Sensor Networks

International Journal of

Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014

International Journal of

ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 201

Applied Computational Intelligence and Soft Computing

thinspAdvancesthinspinthinsp

Artificial Intelligence

HindawithinspPublishingthinspCorporationhttpwwwhindawicom Volumethinsp2014

Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Hindawi Publishing Corporation

httpwwwhindawicom Volume 2014

Advances in

Multimedia

International Journal of

Biomedical Imaging

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 201

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Computational Intelligence and Neuroscience

Industrial EngineeringJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014