1 intelligent information systems on the web and in the aether tim finin university of maryland...

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Intelligent Intelligent Information Systems Information Systems

on the Web on the Web and in the Aetherand in the Aether

Tim FininTim FininUniversity of Maryland University of Maryland

Baltimore CountyBaltimore CountyJoint work with Scott Cost, Benjamin Grosof (MIT), Anupam Joshi, Jim Mayfield (JHU), Charles Nicholas, Yun Peng, Yelena

Yesha & many students.

MAY 2002This work was partially supported by DARPA contract

F30602-97-1-0215, NSF grants CCR007080 and IIS9875433 and grants from IBM, Fujitsu and HP.

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UMBCUMBCan Honors University in an Honors University in

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OverviewOverview

The Problem: building The Problem: building intelligent information systemsintelligent information systems

The Semantic web as part of The Semantic web as part of the solutionthe solution

Some work at UMBCSome work at UMBC Comments and ConclusionsComments and Conclusions


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The problemThe problem

I’ve been engaged in research aimed at I’ve been engaged in research aimed at developing intelligent information systems developing intelligent information systems for thirty years.for thirty years.

The problem is hard, progress is slow, but The problem is hard, progress is slow, but the incremental results are worth it.the incremental results are worth it.

It’s a task for many generations to come.It’s a task for many generations to come. Today’s environment is very different than Today’s environment is very different than

that in 1971.that in 1971.


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They way we were…They way we were…

AN IBM 360 circa 1971AN IBM 360 circa 1971


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They way we will be…They way we will be…


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What’s new?What’s new? Internet.Internet. Virtually of the computers in the Virtually of the computers in the

world have been connected.world have been connected. Scale.Scale. Every day many more computing and Every day many more computing and

communication devices are joining.communication devices are joining. Power.Power. Raw computing power continues to Raw computing power continues to

climb.climb. Wireless.Wireless. New technologies (GSM, 802.11, New technologies (GSM, 802.11,

Bluetooth, UWB?, IR, etc) are creating a Bluetooth, UWB?, IR, etc) are creating a pervasive, ubiquitous computing environmentpervasive, ubiquitous computing environment

Web.Web. The web is like Dennett’s "universal The web is like Dennett’s "universal acid“, a mythical chemical that eats through acid“, a mythical chemical that eats through -- and thus transforms -- everything in its -- and thus transforms -- everything in its path.path.


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IDM ChallengesIDM Challenges

The environment makes new demands and offers The environment makes new demands and offers new challenges, enough to keep all of us busy, new challenges, enough to keep all of us busy, e.g.:e.g.:

Very open environmentsVery open environments Large and diverse community of service and Large and diverse community of service and

content providerscontent providers Lots of relative autonomyLots of relative autonomy Dynamic ad hoc networksDynamic ad hoc networks Systems with widely varying resources -- Systems with widely varying resources --

bandwidth, connectivity, cpu, memory, disk, bandwidth, connectivity, cpu, memory, disk, power, software, knowledge, intelligence, etc.power, software, knowledge, intelligence, etc.


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Research topicsResearch topics

Concepts which can address these challenges Concepts which can address these challenges include:include:

Multiagent systemsMultiagent systems Information and knowledge sharing through common Information and knowledge sharing through common

representation languages, ontologies and protocolsrepresentation languages, ontologies and protocols Automatic service description, discovery, Automatic service description, discovery,

compositioncomposition Negotiation for services and informationNegotiation for services and information Trust based models for authorization, credibility and Trust based models for authorization, credibility and

securitysecurity Social and norm governed behavior Social and norm governed behavior Delegation and degrees of autonomyDelegation and degrees of autonomy Coordination and teamwork modelsCoordination and teamwork models


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Semantic WebSemantic Web

I’ll argue that the semantic web provides a I’ll argue that the semantic web provides a good approach, language and tools to good approach, language and tools to support the development of intelligent support the development of intelligent information systems in this environment.information systems in this environment.

This isn’t obvious, since the SW seems This isn’t obvious, since the SW seems grounded in the “traditional” wired web.grounded in the “traditional” wired web.

But, the principles which drive it are the But, the principles which drive it are the right ones for agents as well as pervasive right ones for agents as well as pervasive computing.computing.

And, by grounding agents in web And, by grounding agents in web technology, they may make it out of the lab.technology, they may make it out of the lab.

Next: overview of Semantic WebNext: overview of Semantic Web


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Origins of the Semantic WebOrigins of the Semantic Web Tim Berners-Lee’s original Tim Berners-Lee’s original

1989 WWW proposal 1989 WWW proposal described a Web of described a Web of relationships among relationships among named objects that unified named objects that unified many many info. management tasks. info. management tasks.

Guha designed MCF at Apple Guha designed MCF at Apple (~94) (~94)

XML+MCF=>RDF (~96)XML+MCF=>RDF (~96) RDF+OO=>RDFS (~99)RDF+OO=>RDFS (~99) RDFS+KR=>DAML+OIL (00)RDFS+KR=>DAML+OIL (00) W3C’s SW activity (01)W3C’s SW activity (01) W3C’s OWL (02?)W3C’s OWL (02?)

http://www.w3.org/History/1989/proposal.html



W3C’s Semantic Web GoalsW3C’s Semantic Web Goals

Focus on machine consumption:Focus on machine consumption:

"The Semantic Web is an extension of the "The Semantic Web is an extension of the current web in which information is given well-current web in which information is given well-defined meaning, better enabling computers defined meaning, better enabling computers and people to work in cooperation."and people to work in cooperation." -- Berners- -- Berners-Lee, Hendler and Lassila, The Semantic Web, Lee, Hendler and Lassila, The Semantic Web, Scientific American, 2001Scientific American, 2001

The current Web The current Web storesstores things whereas the things whereas the semantic Web semantic Web doesdoes things. things.



Semantic Web Semantic Web doesdoes what? what? Concept-based searchConcept-based search

keyword-based searchkeyword-based search Semantic navigationSemantic navigation

link-based navigation link-based navigation PersonalizationPersonalization

one size fits allone size fits all Query answeringQuery answering

document retrievaldocument retrieval

ServicesServices CGI calls, but service-description languages, CGI calls, but service-description languages,

negotiation, negotiation, service composition, etc service composition, etc



Why is this hard?Why is this hard?This is what a web page looks like to a machine

after Frank van Harmelen and Jim Hendler

And understanding natural language is not as hard asunderstanding the images!



OK, so HTML is not helpfulOK, so HTML is not helpful

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Could we tell the machine what the different parts of the text represent?




XML to the rescue?XML to the rescue?

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Some XML fans claim this could be done by adding “meaningful tags” to parts of the text




XML XML machine accessible meaning machine accessible meaning

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But to your machine, the tags still look like this….




Schemas take a step in the right Schemas take a step in the right directiondirection

Schemas help….

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…by relating common termsbetween documents




But other people use other schemasBut other people use other schemas

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Someone else has one like this….after Frank van Harmelen and Jim Hendler



The “semantics” isn’t thereThe “semantics” isn’t there

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…which don’t fit in

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Ontologies can help …Ontologies can help …

An ontology defines the terms used to An ontology defines the terms used to describe and represent an area of describe and represent an area of knowledge. knowledge. Ontologies are used by people, databases, and applications that need to share domain information (a domain is just a specific subject area or area of knowledge, like medicine, tool manufacturing, real estate, automobile repair, financial management, etc.). Ontologies include computer-usable definitions of basic concepts in the domain and the relationships among them ...

They encode knowledge in a domain and They encode knowledge in a domain and also knowledge that spans domains. also knowledge that spans domains. In this way, they make that knowledge reusable.

Working Draft, Web Ontology Working Group.



Ontologies can help …Ontologies can help …

Catalog/ID

GeneralLogical

constraints

Terms/glossary

Thesauri“narrower

term”relation

Formalis-a

Frames(properties)

Informalis-a

Formalinstance

Value Restriction

Disjointness, Inverse,part of…

After Deborah L. McGuinness (Stanford)After Deborah L. McGuinness (Stanford)

SimpleTaxonomies

ExpressiveOntologies



By providing “external” referents to By providing “external” referents to merge onmerge on

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SW languages addmappings and structure.

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TBL’s semantic web vision“The Semantic Web will globalize KR, just as the WWW globalize hypertext” -- Tim Berners-Lee

you arehere



Semantic web languages todaySemantic web languages today

Today there are just two semantic web Today there are just two semantic web languageslanguages DAML – Darpa Agent Markup LanguageDAML – Darpa Agent Markup Language

http://www.daml.org/http://www.daml.org/ RDF – Resource Description FrameworkRDF – Resource Description Framework

http://www.w3.org/RDF/http://www.w3.org/RDF/ and one under development by the W3Cand one under development by the W3C

OWL – Ontology Web LanguageOWL – Ontology Web Languagehttp://www.w3.org/2001/sw/http://www.w3.org/2001/sw/

with more to come, IMHOwith more to come, IMHO



RDF is the first SW languageRDF is the first SW language

<rdf:RDF ……..> <….> <….></rdf:RDF>

XML Encoding Graph

stmt(docInst, rdf_type, Document)stmt(personInst, rdf_type, Person)stmt(inroomInst, rdf_type, InRoom)stmt(personInst, holding, docInst)stmt(inroomInst, person, personInst)

Triples

RDFData Model

Good for Machine

Processing

Good For HumanViewing

Good For Reasoning



Simple RDF ExampleSimple RDF Example

http://umbc.edu/~finin/talks/idm02/“Intelligent Information Systemson the Web and in the Aether”

http://umbc.edu/

dc:Title

dc:Creator

bib:Aff

“Tim Finin” “[email protected]”

bib:namebib:email



XML encoding for RDFXML encoding for RDF<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"

xmlns:dc="http://purl.org/dc/elements/1.1/"

xmlns:bib="http://daml.umbc.edu/ontologies/bib/">

<description about="http://umbc.edu/~finin/talks/idm02/"> <dc:title>Intelligent Information Systems on the Web and in the

Aether</dc:Title> <dc:creator> <description> <bib:Name>Tim Finin</bib:Name> <bib:Email>[email protected]</bib:Email> <bib:Aff resource="http://umbc.edu/" /> </description> </dc:Creator></description></rdf:RDF>

“[email protected]”



N triple representationN triple representation

RDF expressions can also be encoded as a set of RDF expressions can also be encoded as a set of triplestriples. .

<<subjectsubject> <> <predicatepredicate> <> <objectobject> .> . <http://umbc.edu/~finin/talks/idm02/> <http://umbc.edu/~finin/talks/idm02/>

<http://purl.org/dc/elements/1.1/Title> <http://purl.org/dc/elements/1.1/Title> "Intelligent Information Systems on the Web and in the Aether" ."Intelligent Information Systems on the Web and in the Aether" ._:j10949 <http://daml.umbc.edu/ontologies/bib/Name> "Tim Finin" ._:j10949 <http://daml.umbc.edu/ontologies/bib/Name> "Tim Finin" ._:j10949 <http://daml.umbc.edu/ontologies/bib/Email> "[email protected]" ._:j10949 <http://daml.umbc.edu/ontologies/bib/Email> "[email protected]" ._:j10949 <http://daml.umbc.edu/ontologies/bib/Aff> <http://umbc.edu/> ._:j10949 <http://daml.umbc.edu/ontologies/bib/Aff> <http://umbc.edu/> ._:j10949 <http://www.w3.org/1999/02/22-rdf-syntax-ns#type> _:j10949 <http://www.w3.org/1999/02/22-rdf-syntax-ns#type>

<Description> .<Description> .<http://umbc.edu/~finin/talks/idm02/> <http://umbc.edu/~finin/talks/idm02/>

<http://purl.org/dc/elements/1.1/Creator> _:j10949 .<http://purl.org/dc/elements/1.1/Creator> _:j10949 .<http://umbc.edu/~finin/talks/idm02/> <http://www.w3.org/1999/02/22-<http://umbc.edu/~finin/talks/idm02/> <http://www.w3.org/1999/02/22-

rdf-syntax-ns#type> <Description> .rdf-syntax-ns#type> <Description> . Note the generated ID for the anonymous nodeNote the generated ID for the anonymous node



Triple NotesTriple Notes RDF triples have one of two forms:RDF triples have one of two forms:

<URI> <URI> <URI><URI> <URI> <URI> <URI> <URI> <quoted string><URI> <URI> <quoted string>

Triples are also easily mapped into logicTriples are also easily mapped into logic <subject> <predicate> <object><subject> <predicate> <object> <predicate>(<subject>,<object>)<predicate>(<subject>,<object>) With type(<S>,<O>) becoming <O>(<S>)With type(<S>,<O>) becoming <O>(<S>) Example:Example:

subclass(man,person)subclass(man,person) sex(man,male)sex(man,male) domain(sex,animal)domain(sex,animal) man(adam)man(adam) age(adam,100)age(adam,100)

Triples can be easily stored and managed in a Triples can be easily stored and managed in a DBMSDBMS

; Note: we’re not ; showing the actual ; URIs for clarity



RDF Schema (RDFS)RDF Schema (RDFS)

RDF Schema adds RDF Schema adds taxonomies for taxonomies for classesclassesand propertiesand properties subClass and subPropertysubClass and subProperty

and some metadata.and some metadata. domain and rangedomain and range

constraints on propertiesconstraints on properties Several widely usedSeveral widely used

KB tools can importKB tools can importand export in RDFSand export in RDFS Stanford Protégé KB editorStanford Protégé KB editor



RDFS supports simple inferencesRDFS supports simple inferences An RDF ontology plus some RDF An RDF ontology plus some RDF

statements may imply additional RDF statements may imply additional RDF statements.statements.

This is not true of XML.This is not true of XML. Example:Example:

subproperty(mother,parent)subproperty(mother,parent)

domain(parent,person)domain(parent,person)

range(parent,person)range(parent,person)

mother(eve,cain)mother(eve,cain)

Implies:Implies: parent(eve,cain) person(eve) person(cain)

Implies:Implies: parent(eve,cain) person(eve) person(cain)



RDF is being usedRDF is being used

RDF is being used in a number of W3C RDF is being used in a number of W3C specificationsspecifications CC/PP (Composite Capabilities/Preference CC/PP (Composite Capabilities/Preference

Profiles, http://www.w3.org/Mobile/CCPP/)Profiles, http://www.w3.org/Mobile/CCPP/) P3P (Platform for Privacy Preferences Project, P3P (Platform for Privacy Preferences Project,

http://www.w3.org/P3P/http://www.w3.org/P3P/)) Other web standardsOther web standards

RSS 1.0 (Rich Site Summary)RSS 1.0 (Rich Site Summary) RDF calendar (~ iCalendar in RDF)RDF calendar (~ iCalendar in RDF)

Other systemsOther systems MozillaMozilla



RDF is not enough, but a good RDF is not enough, but a good foundationfoundation

RDF lacks expressive adequacy for many RDF lacks expressive adequacy for many taskstasks Only range/domain constraints (on properties)Only range/domain constraints (on properties) No properties of properties (transitive, inverse etc.)No properties of properties (transitive, inverse etc.) No equivalence, disjointness, coverings, etc.No equivalence, disjointness, coverings, etc. No necessary and sufficient conditionsNo necessary and sufficient conditions No rules, axioms, logical constraintsNo rules, axioms, logical constraints

DAML+OIL extends RDFDAML+OIL extends RDF Layering makes partial knowledge available to Layering makes partial knowledge available to

applications which only understand RDFapplications which only understand RDF NB: Building on RDF has some disadvantagesNB: Building on RDF has some disadvantages



We’re going down a familiar roadWe’re going down a familiar road

KR trendsKR trends

55-65: arbitrary data 55-65: arbitrary data structuresstructures

65-75: semantic 65-75: semantic networksnetworks

75-85: simple frame 75-85: simple frame systemssystems

85-95: description logics85-95: description logics 95-??: logic95-??: logic

Web trendsWeb trends

95-97: 95-97: XML XML as as arbitrary structuresarbitrary structures

97-98: 97-98: RDFRDF 98-99: 98-99: RDFSRDFS (schema) (schema)

as a frame-like systemas a frame-like system 00-01: 00-01: DAML+OILDAML+OIL 02-??: DAML-L02-??: DAML-L

Only much faster!



DAML+OIL as a Semantic Web DAML+OIL as a Semantic Web LanguageLanguage

DAML = Darpa Agent Markup LanguageDAML = Darpa Agent Markup Language DARPA program with 17 projects & an integrator DARPA program with 17 projects & an integrator

developing language spec, tools, applications for developing language spec, tools, applications for SW.SW.

OIL = Ontology Inference LayerOIL = Ontology Inference Layer An EU effort aimed at developing a layered An EU effort aimed at developing a layered

approach to representing knowledge on the web.approach to representing knowledge on the web.ProcessProcess

Joint Committee: US DAML and EU Semantic Web Joint Committee: US DAML and EU Semantic Web Technologies participants Technologies participants

DAML+OIL specs released 01/01 & 03/01DAML+OIL specs released 01/01 & 03/01 See http://www.daml.org/See http://www.daml.org/ W3C SW activity started 08/01.W3C SW activity started 08/01.

DAML+OIL



A Simple DAML ExampleA Simple DAML Example

<rdfs:Class about="#Animal"/><rdfs:Class about="#Animal"/>

<rdfs:Class about="#Plant"><rdfs:Class about="#Plant">

<daml:disjointFrom<daml:disjointFrom resource="#Animal"/> resource="#Animal"/>

</rdfs:Class></rdfs:Class>

Note the mixture of rdf (Note the mixture of rdf (plant and animal are classes) plant and animal are classes) and DAMLand DAML (plant and animal are (plant and animal are disjoint)disjoint)



DAML+OIL DAML+OIL RDF RDF

DAML+OIL ontology is a set of RDF statementsDAML+OIL ontology is a set of RDF statements DAML+OIL defines semantics for certain statementsDAML+OIL defines semantics for certain statements Does Does NOTNOT restrict what can be said restrict what can be said

Ontology can include arbitrary RDFOntology can include arbitrary RDF But no semantics for non-DAML+OIL statementsBut no semantics for non-DAML+OIL statements

Adds capabilities common to description logics:Adds capabilities common to description logics: cardinality constraints, defined classes (=> classification), cardinality constraints, defined classes (=> classification),

equivalence, local restrictions, disjoint classes, etc.equivalence, local restrictions, disjoint classes, etc.

More support for ontologiesMore support for ontologies Ontology imports ontologyOntology imports ontology

But not (yet) variables, quantification, and But not (yet) variables, quantification, and general rulesgeneral rules



DAML in One SlideDAML in One Slide<rdf:RDF xmlns:rdf ="http://w3.org/22-rdf-syntax-ns#"<rdf:RDF xmlns:rdf ="http://w3.org/22-rdf-syntax-ns#" xmlns:rdfs="http://w3.org/rdf-schema#"xmlns:rdfs="http://w3.org/rdf-schema#" xmlns:daml="http://daml.org/daml+oil#“>xmlns:daml="http://daml.org/daml+oil#“><daml:Ontology rdf:about=""><daml:Ontology rdf:about=""> <daml:imports rdf:resource="http://daml.org/daml+oil"/><daml:imports rdf:resource="http://daml.org/daml+oil"/></daml:Ontology></daml:Ontology><rdfs:Class rdf:ID="Person"><rdfs:Class rdf:ID="Person"> <rdfs:subClassOf rdf:resource="#Animal"/><rdfs:subClassOf rdf:resource="#Animal"/> <rdfs:subClassOf><rdfs:subClassOf> <daml:Restriction><daml:Restriction> <daml:onProperty rdf:resource="#hasParent"/><daml:onProperty rdf:resource="#hasParent"/> <daml:toClass rdf:resource="#Person"/><daml:toClass rdf:resource="#Person"/> </daml:Restriction></daml:Restriction> </rdfs:subClassOf></rdfs:subClassOf> <rdfs:subClassOf><rdfs:subClassOf> <daml:Restriction daml:cardinality="1"><daml:Restriction daml:cardinality="1"> <daml:onProperty rdf:resource="#hasFather"/><daml:onProperty rdf:resource="#hasFather"/> </daml:Restriction> </rdfs:subClassOf> </rdfs:Class></daml:Restriction> </rdfs:subClassOf> </rdfs:Class><Person rdf:about=“http://umbc.edu/~finin/"><Person rdf:about=“http://umbc.edu/~finin/"><rdfs:comment>Finin is a person.</rdfs:comment><rdfs:comment>Finin is a person.</rdfs:comment></Person></Person>

DAML is built on top of XML and RDF

It can be used to add metadata about anything which has a URI.

everything has URI

DAML is ~= a frame based knowledge representation language

It allows the definition, sharing, composition and use of ontologies

URIs are a W3C standard generalizing URLs



DAML-SDAML-S

DAML-S is an ontology for describing DAML-S is an ontology for describing properties and capabilities of web services properties and capabilities of web services

Desiderata:Desiderata: Ease of expressivenessEase of expressiveness Enables automation of service use by Enables automation of service use by

agentsagents Enables reasoning about service Enables reasoning about service

properties and capabilitiesproperties and capabilities Also appropriate for describing services in Also appropriate for describing services in

a mobile/pervasive computing a mobile/pervasive computing environmentenvironment

See http://daml.org/services/See http://daml.org/services/



DAML-S componentsDAML-S components

Service profile (what it does)Service profile (what it does) For service registration, discovery and matching.For service registration, discovery and matching. High-level description of service and provider with a (human readable) High-level description of service and provider with a (human readable)

description of service, a specification of functionalities provided and other description of service, a specification of functionalities provided and other functional attributes.functional attributes.

Service model (how it works)Service model (how it works) For service invocation, composition, interoperation, monitoring.For service invocation, composition, interoperation, monitoring. A service has inputs, outputs, preconditions and effects. A service has inputs, outputs, preconditions and effects. Composite processes are build using sequence, if-then-else, fork, etc.Composite processes are build using sequence, if-then-else, fork, etc.

Service grounding (how to access)Service grounding (how to access) Specification of service access information (communication protocols, Specification of service access information (communication protocols,

transport mechanisms, etc.) which could be via SOAP, HTTP forms, Java transport mechanisms, etc.) which could be via SOAP, HTTP forms, Java

RMI, RPC, etc.RMI, RPC, etc.



SW is work in progressSW is work in progress

There are important language aspects There are important language aspects which need more work: rules, queries, etc.which need more work: rules, queries, etc.

Many tools need to be createdMany tools need to be created E.g., Protégé plug-in for DAML+OILE.g., Protégé plug-in for DAML+OIL

Applications need to be exploredApplications need to be explored The W3C is developing a new SW languageThe W3C is developing a new SW language

OWL: Ontology Web LanguageOWL: Ontology Web Language ……



W3C Web OntologyW3C Web OntologyWorking GroupWorking Group

The WOWG is working to create aThe WOWG is working to create arecommendation for the "Web Ontology recommendation for the "Web Ontology Language": OWL Language": OWL

51 Members from 30 W3C Organizations 51 Members from 30 W3C Organizations Companies:Companies: Agfa, Daimler-Chrysler, EDS, Fujitsu, Hewlett- Agfa, Daimler-Chrysler, EDS, Fujitsu, Hewlett-

Packard, IBM, Intel, IVIS, Lucent, Network Inference, Nisus, Packard, IBM, Intel, IVIS, Lucent, Network Inference, Nisus, Nokia, Philips, Stilo, Sun, Unisys Nokia, Philips, Stilo, Sun, Unisys

Public Sector:Public Sector: DISA, Electricite de France, Intelink, INTAP, DISA, Electricite de France, Intelink, INTAP, MITRE, NIST MITRE, NIST

Research projects/Labs:Research projects/Labs: DFKI, FZI, Ibrow group, Stanford, DFKI, FZI, Ibrow group, Stanford, U. Bristol, U. Maryland, U. Southhampton U. Bristol, U. Maryland, U. Southhampton

Invited Experts:Invited Experts: Medical, Digital Library, Defense, Medical, Digital Library, Defense, Technical Technical

CoChairs: Jim Hendler, University of Maryland/MIND; CoChairs: Jim Hendler, University of Maryland/MIND; Guus Schreiber, Univ of Amsterdam/IbrowGuus Schreiber, Univ of Amsterdam/Ibrow

http://www.w3.org/2001/sw/WebOnt/http://www.w3.org/2001/sw/WebOnt/



OWL GoalsOWL Goals

The WOWG has identified the The WOWG has identified the following goals in developing OWLfollowing goals in developing OWL Shared ontologies Shared ontologies Ontology evolution Ontology evolution Ontology interoperability Ontology interoperability Inconsistency detection Inconsistency detection Balance of expressivity and scalability Balance of expressivity and scalability Ease of use Ease of use XML syntax XML syntax Internationalization Internationalization



KR meets the WebKR meets the Web

One way to think about the semanticOne way to think about the semanticweb is that we are creating a knowledge web is that we are creating a knowledge representation language for the Web.representation language for the Web.

This is more than just selecting an This is more than just selecting an appropriate KR language and selecting appropriate KR language and selecting an XML encoding.an XML encoding.

The Web as an information system has The Web as an information system has many significant properties.many significant properties. Highly distributed Many content providers Dynamic Evolving Inconsistent …



Semantic Web PrinciplesSemantic Web Principles Everything is on the webEverything is on the web

People, places, times, things all have URIsPeople, places, times, things all have URIs Partial information is assumedPartial information is assumed

The web privileges scalability over integrity and there’s The web privileges scalability over integrity and there’s always more and new stuff to findalways more and new stuff to find

Trust models are criticalTrust models are critical It’s not all trueIt’s not all true

Support information evolutionSupport information evolution Content and consensus is dynamicContent and consensus is dynamic

Minimalist designMinimalist design Make the simple things simple, and the complex things Make the simple things simple, and the complex things

possible. Standardize no more than is necessary.possible. Standardize no more than is necessary. Common data modelCommon data model

To support interoperability and knowledge sharingTo support interoperability and knowledge sharing

Adapted from Eric Miller, W3C



Some UMBC applicationsSome UMBC applications

(1)(1) Semantic web and agents Semantic web and agents (ITTalks) (ITTalks)

(2)(2) Information retrieval on the SW Information retrieval on the SW

(3)(3) Service discovery and Service discovery and composition in ad hoc mobile composition in ad hoc mobile environmentsenvironments

(4)(4) Distributed trust Distributed trust



(1)(1) ITALKS ITALKS

• ITTALKS ITTALKS is a database driven webis a database driven website of IT related talks at UMBC andsite of IT related talks at UMBC andother institutions. The database other institutions. The database contains information oncontains information on– Seminar eventsSeminar events– People (speakers, hosts, users, …)People (speakers, hosts, users, …)– Places (rooms, institutions, …)Places (rooms, institutions, …)

• Web pages with DAML markup are generatedWeb pages with DAML markup are generated• The DAML markup supports agent-based The DAML markup supports agent-based

services relating to these talks.services relating to these talks. Users get talk announcements based on the Users get talk announcements based on the

interests, locations and schedules.interests, locations and schedules.

http://ittalks.org/



humanview



machineview



ITTALKS ArchitectureITTALKS Architecture

Web server + Java servlets

DAMLreasoning

engine

DAMLreasoning

engine

<daml></daml>

<daml></daml>

<daml></daml>

<daml></daml>

DAML files

Agents

Databases

People

RDBMSRDBMSDB

Email, HTML, SMS, WAP

FIPA ACL, KQML, DAML

SQLHTTP, KQML, DAML, Prolog

MapBlast, CiteSeer,Google, …HTTP

HTTP, WebScraping

WebServices

ApacheTomcat



ITTALKS OntologiesITTALKS Ontologies

We’ve defined and use the following We’ve defined and use the following ontologies, all at ontologies, all at http://daml.umbc.edu/ontologies/http://daml.umbc.edu/ontologies/ calendar-ont.daml – calendar-ont.daml – calendar and schedule calendar and schedule

infoinfo classification.daml classification.daml – ACM CCS topics– ACM CCS topics person-ont.daml person-ont.daml – people and their attributes– people and their attributes place-ont.daml place-ont.daml – talk locations– talk locations profile-ont.daml – profile-ont.daml – user modeling infouser modeling info talk-ont.daml – talk-ont.daml – talks infotalks info topic-ont.daml – topic-ont.daml – topics and intereststopics and interests



Two Advanced CapabilitiesTwo Advanced Capabilities

I’ll briefly describe two advanced I’ll briefly describe two advanced capabilities facilitated by DAML:capabilities facilitated by DAML: Classifying talk topics and user Classifying talk topics and user

interests using DAML ontologiesinterests using DAML ontologies Using DAML as a communication Using DAML as a communication

language among software agentslanguage among software agents



What are talks about?What are talks about?

Topic hierarchies provide Topic hierarchies provide indexing termsindexing terms ACM CCS topic hierarchyACM CCS topic hierarchy Open DirectoryOpen Directory

Encoded as DAML ontologiesEncoded as DAML ontologies These allow users to specify interests as well as These allow users to specify interests as well as

browse the database of talks by topicbrowse the database of talks by topic Automatic classification of talks (based on title Automatic classification of talks (based on title

and abstract) and abstract) and users (based on his web and users (based on his web pages, CV, papers, etc.)pages, CV, papers, etc.)

Discovery of mapping rules between CCS to OD Discovery of mapping rules between CCS to OD ontologies using IR techniquesontologies using IR techniques



Classifying TalksClassifying Talks

ACM CCS Ontology

Training corpus

CMU Bow

statisticaltext analysis

tools

CMU Bow


tools

ACM CCSclassifier

Now is the time for all good men to come to the aid of the country. Now is the time for

topics

e.g.: ACMCCS

e.g.:5K ACMabstracts

Topics Ontology

uses

uses



Mapping between topic Mapping between topic ontologiesontologies

Topic ontology T1

Training corpus T1

CMU Bow


tools

CMU Bow


tools

T1T2mapper

{(t2:bar, 0.8), (t2:qux, 0.7), …}

Topic ontology T2

Training corpus T2

T1

T2

t1:foo



Interactive ontology mapperInteractive ontology mapper

Users create maps Users create maps between ontologies between ontologies with URIs to text with URIs to text describing classes & describing classes & properties.properties.

Automates mapping Automates mapping process, taking into process, taking into account hierarchical account hierarchical relationships and relationships and user-specified user-specified landmark landmark mappings.mappings.

Text classification Text classification used to compute used to compute similarities between similarities between pairs of classes or pairs of classes or properties.properties.

A probabilistic A probabilistic approach used to approach used to combine hierarchical combine hierarchical information.information. Used in XTalks to enable mappings between

Alternative topic ontologies in DAML+OIL



DAML and AgentsDAML and Agents

Much multi-agent systems work is grounded in Much multi-agent systems work is grounded in Agent Communication Languages (e.g., KQML, Agent Communication Languages (e.g., KQML, FIPA) and associated software infrastructure such FIPA) and associated software infrastructure such as the DARPA Gridas the DARPA Grid The paradigm has been peer-to-peer message oriented The paradigm has been peer-to-peer message oriented

communication mediated by brokers and facilitators.communication mediated by brokers and facilitators. The DAML program invites different paradigms The DAML program invites different paradigms

which will require some changes in ACLs and which will require some changes in ACLs and their associates software systems.their associates software systems. Agents “publish” beliefs, requests, and other “speech Agents “publish” beliefs, requests, and other “speech

acts” on web pages.acts” on web pages. Agents “discover” what peers have published on the Agents “discover” what peers have published on the

web.web. The software agent research community is very The software agent research community is very

interested in the semantic web and DAMLinterested in the semantic web and DAML

ask-all

advertisesubscribe


MarylandMaryland 5959MS Outlook

XSBDAML+OIL

Reasoner

ITTALKSagent

Travelagent

Calendaragent

Useragent

BrokerAgent

AgentNameServer

user’s daml profile

mapquest

MS Outlook

ITTALKS app

Common agent infrastructure

FIPA ACL

API

Communicationprotocol

1

8

7 6

5

3

2

4

9

10

11

12

13

17

16

15

14

18



How does DAML Help?How does DAML Help?

ontologylanguage

usermodels

interoplanguage

agentcommunication

servicedescriptionlanguage

DAML+OIL provided a uniform language which metMany needs in developing a complex application.



XTalks Personal AgentXTalks Personal Agent

XPA is a configurable “personal agent” which XPA is a configurable “personal agent” which accepts FIPA messages from XTalks and other accepts FIPA messages from XTalks and other instances of XPAs as well as applications, e.g. MS instances of XPAs as well as applications, e.g. MS Outlook.Outlook.

JADE platformJADE platform

PersonalAgent

Infrastructure

PluginManager

UserInterface

UserModelCOM

Bridge

RuleEngine

Interface

XSB

Jess

yajxb

XtalksPlugin

MapquestPlugin

BuddyList

Plugin

ExternalPlugins

External World



Xtalks agentsXtalks agents

XtalksSystem

Xtalks Interface

Xtalks Agent

Mapquest Agent

Personal Agent (1)

FIPA RequestResponse Protocol

FIPA RequestResponse Protocol

Periodicquerying

Scenarios1,2

Personal Agent (2)

Personal Agent (3)

Scenarios3,4

1 – Xtalks Announcement2 – User Agent Solicitation3 – Buddy List4 – Travel Planning

XtalksSystem



Damlator translation engineDamlator translation engine

Extensible engine for DAML-encoded Extensible engine for DAML-encoded Semantic Web pages translation and cachingSemantic Web pages translation and caching Currently supported output formats:Currently supported output formats:

For humans: GIF and PNGFor humans: GIF and PNG For agents: DAML, NTriples, Prolog termsFor agents: DAML, NTriples, Prolog terms

Caching supports scalability and efficiencyCaching supports scalability and efficiency Incorporated as an Apache-moduleIncorporated as an Apache-module

Faster, application/user independent and system-wide Faster, application/user independent and system-wide availabilityavailability

Accessed via Accessed via http://host/@SeeAs@/original/path/to/file.damlhttp://host/@SeeAs@/original/path/to/file.daml

Similar to W3C RDF Similar to W3C RDF Validation ServiceValidation Service Uses Jena RDF/XML Parser, Uses Jena RDF/XML Parser,

Apache Xerces, AT&T GraphVizApache Xerces, AT&T GraphViz Available from Available from

http://www.ittalks.org/download/http://www.ittalks.org/download/

HTTPBrowser

DAML-speaking

Agent

Apache WebServer

DAMLATORModule

Local File SystemDAMLATOR

Cache



How does DAML Help?How does DAML Help?

ontologylanguage

usermodels

interoplanguage

agentcommunication

servicedescriptionlanguage

DAML+OIL provided a uniform language which metMany needs in developing a complex application.



(2)(2) Integrating Retrieval and Integrating Retrieval and InferenceInference

Problem:Problem: How do we do information retrieval over How do we do information retrieval over documents and queries which combine free text documents and queries which combine free text and semantic web markup?and semantic web markup? IR systems and KB systems use different modelsIR systems and KB systems use different models

One Solution: One Solution: (1)(1) index both the text and index both the text and markup and then (2) use existing IR systems to markup and then (2) use existing IR systems to find documents that match queriesfind documents that match queries

Issues: Issues: (1) How do we index markup? (2) When (1) How do we index markup? (2) When and where do we do inferencing over the markup?and where do we do inferencing over the markup?

Applications:Applications: (1) Improved recall and precision (1) Improved recall and precision for IR systems, (2) Retrieving documents for for IR systems, (2) Retrieving documents for question answering.question answering.



Student Event ScenarioStudent Event Scenario

UMBC sends out descriptions of ~50 events a UMBC sends out descriptions of ~50 events a week to students.week to students.

Each student has a “standing query” used to Each student has a “standing query” used to route event messages.route event messages. A student only receives announcements of events A student only receives announcements of events

matching his interests and schedule.matching his interests and schedule. Use LMCO’s AeroText system to automatically Use LMCO’s AeroText system to automatically

add DAML+OIL markup to event descriptions.add DAML+OIL markup to event descriptions. Categorize text announcements into event typesCategorize text announcements into event types Identify key elements and add DAML markupIdentify key elements and add DAML markup

Use JESS to reason over the markup, drawing Use JESS to reason over the markup, drawing ontology supported inferencesontology supported inferences



Event OntologyEvent Ontology

A simple ontology A simple ontology for University for University eventsevents

Includes classes, Includes classes, subclasses, subclasses, properties, etc.properties, etc.

Can include Can include instance data, e.g., instance data, e.g., UMBC, NEC, UMBC, NEC, Fairleigh Fairleigh Dickenson, etcDickenson, etc

... ...

... ...

Event_Name

Event_DateStart_Time

End_TimePlace

Organizer

...

Property

KEY:

PropertyAssociation

Subclass Of

Instance Of

EVENT

DATETIME

TRIP SPORTMOVIESHOW

INDIVIDUAL

ATHLETICS CHESSBASKETBALLBASEBALL

CLASS

TEAM



IR EngineIR Engine

We’re experimenting with two IR engines: We’re experimenting with two IR engines: JHU’s Haircut and UMBC’s SIRE, using a JHU’s Haircut and UMBC’s SIRE, using a similar process for both:similar process for both: Convert DAML markup to RDF triplesConvert DAML markup to RDF triples Infer additional triples which follow from modelInfer additional triples which follow from model

(S,type,O) ^ (0,subclass,O2) => (S,type,O2)(S,type,O) ^ (0,subclass,O2) => (S,type,O2) Use domain specific rules to infer additional Use domain specific rules to infer additional

triplestriples ““for a movie, retrieve genre property from IMDB”for a movie, retrieve genre property from IMDB”

Generate 7 indexing terms from each (S,P,O) Generate 7 indexing terms from each (S,P,O) tripletriple

SPO, SP*, S*O, *PO, S**, *P*, **OSPO, SP*, S*O, *PO, S**, *P*, **O Index free text and resulting triple termsIndex free text and resulting triple terms



Event informationin plain text

AeroText+

Java

Generate RDF Triples

JHUHAIRCUT IR Engine

QueryUser

Interface

Filter query on event property

constraints

Inference with DAMLJessKB

DAML/RDF

Markup

RDF Triples

Expanded RDF Triples + Free Text

Event C

ategories

Movie

Sport

Talk

. . .

Trip

HOWLIR FRAMEWORK

Must

OK

Must not

WEB

Results User Interface

StructuredQuery

AgentsExpand Event

Description

Final Results Inference on results

Events



DOCUMENTDOCUMENT<DOC><DOCNO>'http://gentoo.cs.umbc.edu/howlir/announcements/charity#charity_001</DOCNO><TEXT>'UMBC Blood Drive!!Office of Student Life launches its annual Blood Drive for the Red Cross on Mon, Nov 20 in the UC Ballroom from 10am - 4pm. </TEXT><TRIPLE>triple(charity_001)( 'http://gentoo.cs.umbc.edu/howlir/announcements/charity#charity_001_place', 'http://daml.umbc.edu/ontologies/event_ont#Building', 'University Center').triple(charity_001)( 'http://gentoo.cs.umbc.edu/howlir/announcements/charity#charity_001', 'http://daml.umbc.edu/ontologies/event_ont#Organizer', 'Office of Student Life').triple(charity_001)( 'http://gentoo.cs.umbc.edu/howlir/announcements/charity#charity_001_date', 'http://daml.umbc.edu/ontologies/event_ont#Day_of_week', 'Monday'). … </TRIPLE></DOC>



QUERYQUERY<Query><required> triple(query_001)( 'http://daml.umbc.edu/ontologies/query#query_001’, 'http://daml.umbc.edu/ontologies/event_ont#Movie_Name' 'Ocean’s Eleven').</required><allowed></allowed><disallowed>triple(query_001)('http://daml.umbc.edu/ontologies/query#query_001’, 'http://daml.umbc.edu/ontologies/event_ont#Organizer’ ‘SEB'). </disallowed></Query>



Results?Results?

Doing experiments now to measure recall Doing experiments now to measure recall and precision over a small collection of and precision over a small collection of 1500 event announcements and 12 1500 event announcements and 12 queries.queries.

CompareCompare Only free textOnly free text Free text + base triples but no inferencingFree text + base triples but no inferencing Free text + triples + inferred triplesFree text + triples + inferred triples

We expect to see improved precision and We expect to see improved precision and recall recall



(3)(3) Enhancing Bluetooth’s Enhancing Bluetooth’sService Discovery ProtocolService Discovery Protocol

Bluetooth’s SDP is very simpleBluetooth’s SDP is very simple Services and attributes represented by UUIDsServices and attributes represented by UUIDs

which are 128 bit numbers!which are 128 bit numbers! No registration, aggregation, multicasting, No registration, aggregation, multicasting,

event notificationevent notification Enhanced SDP uses DAML+OILEnhanced SDP uses DAML+OIL

We assume at least one resource rich device in We assume at least one resource rich device in the ad hoc network to serve as a matchmakerthe ad hoc network to serve as a matchmaker

Services and attributes described in DAML Services and attributes described in DAML using a “standard” ontologyusing a “standard” ontology

All available information from service and All available information from service and attribute descriptions used for matchingattribute descriptions used for matching

Reasons to obtain Reasons to obtain closestclosest match match

Service

AdHocNetworkService

rdfs:subClassof

OperatingSystem

ProvidedBy

ServiceCost

rdf:Property

rdf:P

rope

rty

ContactURI

ProviderName

NetworkTechnology

PrinterService

rdfs:subClassOf

PrintColorQuality

PrintFileType

PrintSpeed

PrintTechnology

PrintResolution

PrintOutputFormat

Printer

PrinterModel

Priority Value

rdf:Property

rdf:Property rdf:Property

rdfs:su

bC

lassO

f

Priority Value



(4)(4) Delegation Based Model for Distributed Delegation Based Model for Distributed TrustTrust

We are developing a delegation based We are developing a delegation based model for distributed authorization and model for distributed authorization and trust for use in both wired and wireless trust for use in both wired and wireless scenarios.scenarios.

Trust depends on Trust depends on policies + credentials + delegation actions + policies + credentials + delegation actions +

proofs of permissions and obligations.proofs of permissions and obligations. Agents make speech acts about and Agents make speech acts about and

reason over these properties and relations reason over these properties and relations Grounded in an ontology represented in Grounded in an ontology represented in

DAMLDAML



Other UMBC SW workOther UMBC SW work

Context aware computingContext aware computing Service composition in pervasive Service composition in pervasive

computing environmentscomputing environments Intelligent opportunistic data caching in Intelligent opportunistic data caching in

mobile computing environmentsmobile computing environments Using DAML-S in FIPA’s directory facilitatorUsing DAML-S in FIPA’s directory facilitator Ontology mappingOntology mapping Better reasoning toolsBetter reasoning tools



ConclusionsConclusions

Some thoughts…Some thoughts… Solving the symbol grounding Solving the symbol grounding

problemproblem Rethinking agent communicationRethinking agent communication

How do we get thereHow do we get there



The symbol grounding problemThe symbol grounding problem

An argument against human-like AI is An argument against human-like AI is that it’s impossible unless machinesthat it’s impossible unless machinesshare our perception of the world.share our perception of the world.

A solution to this “symbol groundingA solution to this “symbol groundingproblem” is to give robots with humanproblem” is to give robots with humaninspired senses.inspired senses.

But the world we experience is determined by our But the world we experience is determined by our senses, and human and machine bodies may lead senses, and human and machine bodies may lead to different conceptions of the world (e.g. Nagel’s to different conceptions of the world (e.g. Nagel’s What Is It Like To Be a Bat?What Is It Like To Be a Bat? ) )

Maybe the Semantic Web is a way out of this Maybe the Semantic Web is a way out of this problem?problem?

MIT’s Cog



Solving the symbol grounding Solving the symbol grounding problemproblem

The web may become a common world The web may become a common world that both humans and machines can that both humans and machines can understand.understand.

Confession: the web is more familiar and Confession: the web is more familiar and real to me than much of the real world.real to me than much of the real world.

Physical objects can be tagged with low Physical objects can be tagged with low cost (e.g., $0.05) transponders or RFIDs cost (e.g., $0.05) transponders or RFIDs encoding their URIsencoding their URIs See HP’s Cooltown projectSee HP’s Cooltown project

http://cooltown.com/http://cooltown.com/



Rethinking the agent communication Rethinking the agent communication paradigmparadigm

Much multi-agent systems work is grounded Much multi-agent systems work is grounded in Agent Communication Languages (e.g., in Agent Communication Languages (e.g., KQML, FIPA) and associated software KQML, FIPA) and associated software infrastructure.infrastructure. This paradigm was articulated ~1990, about the This paradigm was articulated ~1990, about the

same time as the WWW was developed.same time as the WWW was developed. Our MAS approach has not yet left the laboratory Our MAS approach has not yet left the laboratory

yet the Web has changed the world.yet the Web has changed the world. Maybe we should try something different?Maybe we should try something different?

The communication MAS paradigm has been peer-The communication MAS paradigm has been peer-to-peer message oriented communication to-peer message oriented communication mediated by brokers and facilitators -- an mediated by brokers and facilitators -- an approach inherited from client-server systems.approach inherited from client-server systems.



Rethinking the agent communication Rethinking the agent communication paradigmparadigm

A possible new paradigm?A possible new paradigm? Agents “publish” beliefs, requests, and Agents “publish” beliefs, requests, and

other “speech acts” on web pages.other “speech acts” on web pages. Brokers “search” for and “index” published Brokers “search” for and “index” published

contentcontent Agents “discover” what peers have Agents “discover” what peers have

published on the web and browse for more published on the web and browse for more detailsdetails

Agents “speak for” content on web pages byAgents “speak for” content on web pages by Answering queries about themAnswering queries about them Accepting comments and assertions about themAccepting comments and assertions about them



How do we get there from here?How do we get there from here?

This semantic web emphasizes ontologies This semantic web emphasizes ontologies – their development, use, mediation, – their development, use, mediation, evolution, etc.evolution, etc.

It will take some time to really deliver on It will take some time to really deliver on the agent paradigm, either on the Internet the agent paradigm, either on the Internet or in a pervasive computing environment.or in a pervasive computing environment.

The development of complex systems is The development of complex systems is basically an evolutionary process.basically an evolutionary process.

Random search carried out by tens of Random search carried out by tens of thousands of researchers, developers and thousands of researchers, developers and graduate students.graduate students.



Climbing Mount ImprobableClimbing Mount Improbable

““The sheer height of the The sheer height of the peak doesn't matter, so peak doesn't matter, so long as you don't try to long as you don't try to scale it in a single scale it in a single bound. Locate the mildly bound. Locate the mildly sloping path and, if you sloping path and, if you have unlimited time, the have unlimited time, the ascent is only as ascent is only as formidable as the next formidable as the next step.”step.” -- Richard -- Richard Dawkins, Climbing Dawkins, Climbing Mount Improbable, Mount Improbable, Penguin Books, 1996.Penguin Books, 1996.



The Evolution of Useful ThingsThe Evolution of Useful Things

The Evolution of Useful The Evolution of Useful ThingsThings, Henry Petroski, , Henry Petroski, 1994.1994.

Prior to the 1890’s, papers Prior to the 1890’s, papers were held together with were held together with straight pens.straight pens.

The development of “spring The development of “spring steel” allowed the invention steel” allowed the invention of the paper clip in 1899.of the paper clip in 1899.

It took about It took about 25 years (!)25 years (!) for for the evolution of the modern the evolution of the modern “gem paperclip”, “gem paperclip”, considered to be optimal for considered to be optimal for general use.general use.



So, we should …So, we should …

Start with the simple and move toward the complexStart with the simple and move toward the complex E.g., from vocabularies to FOL theoriesE.g., from vocabularies to FOL theories

Allow many ontologies to bloom Allow many ontologies to bloom Let natural evolutionary processes select the Let natural evolutionary processes select the

most useful as common consensus ontologies.most useful as common consensus ontologies. Support diversity in ontologiesSupport diversity in ontologies

Monocultures are unstableMonocultures are unstable There should be no THE ONTOLOGY FOR X.There should be no THE ONTOLOGY FOR X.

The evolution of powerful, machine readable The evolution of powerful, machine readable ontologies will happen over multiple human ontologies will happen over multiple human generationsgenerations Incremental benefits will more than pay for effortIncremental benefits will more than pay for effort



For more informationFor more information On RDFOn RDF

http://www.w3.org/RDF/http://www.w3.org/RDF/ On DAMLOn DAML

http://www.daml.org/http://www.daml.org/ On W3C’s semantic web activityOn W3C’s semantic web activity

http://www.w3.org/2001/sw/http://www.w3.org/2001/sw/ On the semantic webOn the semantic web

http://semanticweb.org/http://semanticweb.org/ On our work at UMBCOn our work at UMBC

http://research.ebiquity.org/http://research.ebiquity.org/

1 intelligent information systems on the web and in the aether tim finin university of maryland...

Documents

beumbcan honors university

maryland origins

maryland semantic webill

maryland whats new

maryland overviewthe

web of relationships

web technology

traditional wired web