244

Copyright © 2009, IGI Global, distributing in print or electronic forms without written permission of IGI Global is prohibited.

Chapter 2.9An Ontological Approach to

Managing Project Memories in Organizations

Davy MonticoloSeT Laboratory, University of Technology UTBM, France

Vincent HilaireSeT Laboratory, University of Technology UTBM, France

Samuel GomesSeT Laboratory, University of Technology UTBM, France

Abderrafiaa KoukamSeT Laboratory, University of Technology UTBM, France

AbstrAct

Knowledge Management (KM) is considered by many organizations a key aspect in sustaining competitive advantage. In the mechanical design domain, the KM facilitates the design of routine product and brings a saving time for innovation. This chapter describes the specification of a project memory as an organizational memory to specify knowledge to capitalize all along project in order to be reuse. Afterwards it presents the design of a domain ontology and a multi agent system to

manage project memories all along professional activities. As a matter of fact, these activities require that engineers, with different specialities, collaborate to carry out the same goal. Inside professional activities; they use their know-how and knowledge in order to achieve the laid down goals. The professional actors competences and knowledge modeling allows the design and the description of agents’ know-how. Furthermore, the paper describes the design of our agent model based on an organisational approach and the role of a domain ontology called OntoDesign to manage heterogeneous and distributed knowledge.

245

An Ontological Approach to Managing Project Memories in Organizations

IntroductIon

In today’s challenging global market, companies have to innovate in order to improve competitive-ness and business performance. They must bring innovative products to market more effectively and more quickly to maximize customer interest and sales. The pressure to reduce time, improve product quality, and lower costs have not gone away; they are being reaffirmed and folded into programs that focus on delivering the “right” product. Product leadership companies must continue to enter new markets with innovative products. This requires leveraging and reusing the product-related intellectual capital created by partners working together. Business innovation must occur in several dimensions including proj-ect organization, product definition, production engineering, ergonomics design, environmental impacts, and so forth.

In addition, the information technology explo-sion led to a shift in the economy and market rules forcing corporations to adapt their organization and management in order to improve their reac-tion and adaptation time. Information systems became backbones of organizations enabling project-oriented management and virtual teams, therefore the industrial interest in methodologies and tools enabling capitalization and management of organizational knowledge grew stronger. An organizational memory is “an explicit, disembod-ied and persistent representation of knowledge and information in an organization, in order to facilitate their access and reuse by members of the organization” (Gandon, 2002). The stake in building an organizational memory management system is the coherent integration of this dispersed knowledge in a corporation with the objective to promote knowledge growth, promote knowledge communication and in general preserve knowl-edge within an organization (Rabarijaona, 2001). This memory, explaining the organizational knowledge may be considered as a knowledge

base of the organization. Such knowledge base can be restricted to the project world and so be called project memory. The project memory is a memory of knowledge and information acquired and produced during the realization of the projects (Matta, 2000). Thus, project memories constitute a basis for knowledge capitalization and reuse (Bekhti, 2003).

It is necessary to define the nature of this organizational knowledge before to present a knowledge management system. Starting from the bottom, we use the definition of knowledge information and data of Weggeman (1996) and Fukuda (1995):

• Data is a perception, a signal, a sign or a quantum of interaction (e.g., ‘200’ or ‘L’ are data). Data is symbolic representation of numbers, fact, quantities; an item of data is what a natural or artificial sensor indicates about a variable;

• Information is data structured according to a convention (e.g., L=200mm). Informa-tion is the result of the comparison of data which are situationally structured in order to arrive at a message that is significant in a given context. Information is obtained from data which have been given significance and selected as useful.

• Knowledge is information with a context and value that make it usable (e.g., ‘the shutter line out as a length L=200mm’). Knowledge is what places someone in the position to perform a particular task by selecting, interpreting and evaluation information depending on the context. Knowledge is an information which was interpreted (i.e., the intended meaning of which was decided) in context and which meaning was articulated with already acquired knowledge (Fukuda, 1995).

24 more pages are available in the full version of this document, which may

be purchased using the "Add to Cart" button on the product's webpage:

www.igi-global.com/chapter/ontological-approach-managing-project-

memories/8790

This title is available in InfoSci-Books, InfoSci-Social Technologies, InfoSci-

Social Technologies, Business-Technology-Solution, Digital, Social, and

Healthcare Technologies, Digital, Social, and Healthcare Technologies,

InfoSci-Select. Recommend this product to your librarian:

www.igi-global.com/forms/refer-database-to-librarian.aspx?id=8790

Related Content

Web 2.0: Integration Model with Electronic CommerceR. Todd Stephens (2011). Business Organizations and Collaborative Web: Practices, Strategies and

Patterns (pp. 18-30).

www.igi-global.com/chapter/web-integration-model-electronic-commerce/54045

Collaborative Performance: Addressing the ROI of CollaborationKjetil Kristensen and Björn Kijl (2010). International Journal of e-Collaboration (pp. 53-69).

www.igi-global.com/article/collaborative-performance-addressing-roi-collaboration/40254

Integration of E-Collaboration Technologies: research Opportunities and ChallengesBjørn Erik Munkvold and Ilze Zigurs (2005). International Journal of e-Collaboration (pp. 1-24).

www.igi-global.com/article/integration-collaboration-technologies/1929

Small Business Collaboration Through Electronic MarketplacesYin Leng Tan and Linda Macaulay (2008). Encyclopedia of E-Collaboration (pp. 569-576).

www.igi-global.com/chapter/small-business-collaboration-through-electronic/12481