XML + Semantics = DARPA Agent Markup Language _DAML_

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					Principals, Practice & Experience




 XML + Semantics = DARPA Agent
    Markup Language (DAML)

                  William Holmes, Dr. Paul Kogut
                  Management & Data Systems
                  Valley Forge, PA
                  June 4, 2001

                                        JS01 June 4-6, 2001
Principals, Practice & Experience

 Roadmap
   The Semantic Web
   Agents & Ontologies
   Object Management Group (OMG) Initiatives
   The DARPA Agent Markup Language (DAML)
           What is it?
           How does it fit in? / What is its role?
   LM M&DS UML-based Ontology Toolset (UBOT)
           Ontology Design & Consistency Checking
           Automated Annotation via AeroTextTM

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Principals, Practice & Experience

 Semantic Web: The Vision
                     Hi Pete, it’s Lucy. I’m at the doctor’s office.
                                  to see a specialist and
                     Mom needsGreat! I’ll have my agentthen has
                                 set of Hello? therapy
                                         physical
                    to have a seriesup the appointments.sessions.
                                         Sure Lucy.
                      BiweeklyRING … RING ... split the
                                 or something. Can you
                                 chauffeuring with me?




            * Berners-Lee, Hendler, Lassila “The Semantic Web” Scientific American, May 2001
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Principals, Practice & Experience

  The Vision

                                                             Lucy’s agent looks up several lists of
                                                                 providers and checks for ones
                                                              in-plan for Mom’s insurance, within
   Schedule a treatment plan for MomLucy’s agent formulates a schedule
                                                               a 20-mile radius of her home, and
 using Pete and my schedules. Only use appointments for therapists with
                                        of                   with
    providers that are in-plan for Mom’s appointments available a rating of excellent or very good.
                                                       Lucy’s agent retrieves information
                                                                   that fit
  insurance, are within a 20-mile radius, into Pete and Lucy’s schedule.
                                                      about Mom’s prescribed treatment
and have a rating of excellent or very good.               from the doctor’s agent.


                                      Semantic Web



                 * Berners-Lee, Hendler, Lassila “The Semantic Web” Scientific American, May 2001
  Page 4                                                                            JS01 June 4-6, 2001
Principals, Practice & Experience

 That’s Great but How?
   Need Agents
           Definition (Merriam-Webster):
              one who is authorized to act for or in the place of another as a
               business representative
           Provide a means of processing the volumes of
            information found on the web.
   Need Ontologies
           Definition:
              Philosophy -  A theory about the nature of existence.
              A.I. - A formal definition of relations among terms.

           Provide a “semantic grounding” for the web.
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Principals, Practice & Experience

 What are Agents?
   In software, “Agent” is used in many different ways:
              persistent process/daemon:
              mobile code
              autonomous robots
              “intelligent agent” -   what makes it intelligent?
   simple definitions that capture the essence of
          agents:
              an Object that   decides when to say go and when to say no -
               OMG
              “programs that operate at a high enough semantic level that they
               can form new connections to other programs in order to get a job
               done” Burstein, McDermott
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Principals, Practice & Experience

 Why Agents?
     Agents are the next generation of middleware
          – built on top of existing middleware (e.g., CORBA, EJB, Jini)
          – run-time integration via dynamic discovery and resource negotiation
              – emphasis on broker and facilitator agents (e.g. yellow pages)

     Agents are the next generation user interface
          – more complex applications require personal assistant agents
          – multi-modal interfaces e.g. speech, handwriting, gestures
          – user specifies goals and agent handles details according to user
            preferences
                 I need to go to Fort Worth                        Internet / Intranet agents
                 on Monday for 3 days.
                                                                          hotels         car rental
                                              personal assistant
                 itinerary, tickets & maps          agent             maps           airlines
 Page 7                                                                             JS01 June 4-6, 2001
Principals, Practice & Experience

 Why Agents? (Cont.)
   Agents are the next level of component abstraction
           agents are components with attitudes
                beliefs, desires, goals…*

           agents interact like humans via speech acts
                request, inform, promise

           agents share a context for efficient communication
                domain model  ontologies are used at run-time
                ontology agent/services - query, retrieve and translate ontologies




          *Labrou, Finin, Peng “Agent Communication Languages:The Current Landscape” IEEE
                                  Intelligent Systems March/April 1999
 Page 8                                                                           JS01 June 4-6, 2001
Principals, Practice & Experience

 Examples of Agent Applications*
           personal assistant - digital secretary
              – travel arrangements
              – meeting schedule coordination
              – personalized information filtering
              – mobile computing

           internet/intranet information retrieval/summarization
           electronic commerce
           enterprise workflow - e.g., sales, order processing, shipping
           military command and control
           synthetic characters (e.g., Extempo Systems, Virtual Personalities)
           robots - manufacturing, office, domestic
           design and engineering
                   *see Hendler “Is There An Intelligent Agent in Your Future?”
                       http://helix.nature.com/webmatters/agents/agents.html
 Page 9                                                                           JS01 June 4-6, 2001
Principals, Practice & Experience

 Ontologies
    Machine readable semantic specifications.
            Include terms, relations, and inference rules
            What does “capital” mean?
               Seat of government (Tallahassee, Harrisburg, Austin)
               An upper-case letter
               monies, securities, investments, etc…
               the top of a column or pillar.

    XML is Not Enough!!!
            Allows definition of syntax, but not semantics (meaning)
            Can be considered the “Assembly Language” of the Web.

 Page 10                                                           JS01 June 4-6, 2001
Principals, Practice & Experience

 OMG Initiatives
    OMG Agent Platform Special Interest Group (SIG)
            extend the OMG Object Management Architecture (OMA) to better
             support agent technology
            identify and recommend new OMG specifications in the agent area
            recommend agent-related extensions to existing and emerging OMG
             specifications
            promote standard agent modeling techniques
            see http://www.objs.com/agent/index.html
    OMG Ontology Working Group
            Align the domain modeling activities of OMG with the Semantic Web
             initiative of the World Wide Web Consortium and with related
             ontology development projects such as DARPA DAML and IEEE
             SUO (Standard Upper Ontology).
 Page 11                                                          JS01 June 4-6, 2001
Principals, Practice & Experience

 DARPA Agent Markup Language
    Machine-Readable Ontologies & Annotation (markup)
    Aimed at “Resources”, Not just web-pages
            Sensors
            Services
            Appliances
    Lots of industry Buzz*
            Scientific American
            IEEE Distributed Systems
            New York Times
            ZDNet
           …
                                   *See http://www.daml.org/inthenews.html
 Page 12                                                                JS01 June 4-6, 2001
Principals, Practice & Experience

 DAML: Basic Idea
                    queries             DAML                               web
                                       annotation                         pages

                                             links
           web crawlers
                                                         annotate
                                        DAML            manually or
                                       ontologies    semi-automatically


                                             links
                      queries           DAML                                  schema
                                       annotation
                                                                             RDBMS
                      queries
                                                                                 data

           agents   web pages, databases, legacy software, devices, sensors...
                    have annotations linking their terms to ontologies
 Page 13                                                                   JS01 June 4-6, 2001
Principals, Practice & Experience

 DAML Annotation: Extreme Metadata

                           Evolution of Metadata
                        explicit semantic agreements via machine-readable ontologies

  implicit semantic agreements on paper!


                                           Subject verb object
  document                       XML          semantics for         Full semantics
 parsing info    keywords       schema     selected sentences       for all content

    browser     web crawler      XML              agents                agents
                                parsers         (near-term)             (future)



 Page 14                                                                JS01 June 4-6, 2001
Principals, Practice & Experience

 DAML Program
    Main DAML website = www.daml.org
    Duration: August 2000 to Fall 2002
    Approach:
            MIT W3C semantic web activity
               http://www.w3c.org/2001/sw/
               “The semantic Web and itslanguages” in IEEE Intelligent
               Systems, November/December 2000, pages 67-73 available at
               http://www.ksl.Stanford.EDU/projects/DAML/
            Extend XML/RDF
               represent ontologies
               annotate web pages     and other information with links to ontologies
 Page 15                                                               JS01 June 4-6, 2001
Principals, Practice & Experience

 DAML Program (Cont.)
    17 research teams and 1 integration team
            industry, academia and World Wide Web Consortium
            expertise in AI knowledge representation, logic and web
             technologies
            cooperation with European Union IST Program
                 www.daml.org/committee/

    DAML language definition
            Ontology Definition
            Rules Definition




 Page 16                                                               JS01 June 4-6, 2001
Principals, Practice & Experience

 DAML Program (Cont.)
    DAML tools
            ontology development and verification
            web page annotation
            dynamic composition of agent services
            distributed query processing and inference
            ontology translation
    DAML trial applications
            Government: Intelink, Center for Army Lessons Learned
            Commercial: e-commerce, information retrieval




 Page 17                                                             JS01 June 4-6, 2001
Principals, Practice & Experience

 The Origins of DAML
    Extensible Markup Language (XML)
            provides syntactic interoperability
            depends on implicit semantic agreements
    Resource Description Framework (RDF)
            designed to represent metadata for web resources in an XML syntax
            triples: <shoeGen:GovermentOrganization rdf:ID="DARPA”/>
                      <shoeGen:OrganizationHomePage rdf:about="http://www.darpa.mil/">
                        <shoeProj:authorOrg rdf:resource="#DARPA" />
                      </shoeGen:OrganizationHomePage>

    RDF Schema (RDFS)                                                   DAML
            adds OO concepts: class and subclass                        RDFS
                                                                          RDF
           * For more information see www.w3.org                          XML
 Page 18                                                                     JS01 June 4-6, 2001
Principals, Practice & Experience

 Status of DAML
    DAML+Oil (ontology)
            released January 2001 - latest revision March 2001
            language specifications and documentation:
               http://www.daml.org/2001/03/daml+oil-index.html

            design rationale
               http://www.cs.man.ac.uk/~horrocks/Slides/index.html

    DAML-L (logic)
            rule representation and reasoning
            development in progress


 Page 19                                                          JS01 June 4-6, 2001
Principals, Practice & Experience

 UML-Based Ontology Toolset (UBOT)
    We are applying:
            graphical modeling and formal verification techniques from software
             engineering
            text extraction from natural language processing
            lexical semantic resources from cognitive science
    to build a tool-set that supports
            creation, extension and consistency checking of DAML ontologies
            DAML annotation of information resources for agents
    intended for users who have minimal training in knowledge
           representation and agent theory
            see http://ubot.lockheedmartin.com/


 Page 20                                                            JS01 June 4-6, 2001
Principals, Practice & Experience

 UBOT Team
    Lockheed Martin Management & Data Systems
            architecture, development and integration
    Versatile Information Systems (Northeastern
           University)
            formal verification of UML
    Lockheed Martin Advanced Technology Center
            field test of DAML and UBOT
    Kestrel Institute
            automated formal methods

 Page 21                                                 JS01 June 4-6, 2001
Principals, Practice & Experience

 UBOT Architecture: Ontology Engineering
                    UBOT
                                             XMI
                                            models
                                                      UML
                          UML GUI                     DAML
    DAML Ontology                   Consistency       Translation
                       XMI
    Engineer                         checking
                      models
                                      results
                                                                        Extended
                         UML                                            DAML
                                                      Baseline          ontologies
                      Formalization                   DAML
                                                      ontologies
                      Slang            Semantic
                      models        inconsistencies

                         Specware

 Page 22                                                            JS01 June 4-6, 2001
Principals, Practice & Experience

 UBOT Architecture: Annotation
                       UBOT
                                        XMI         UML
                         UML GUI                   DAML
                                                 Translation           corrected
                                                                       annotation
                                uncorrected
                                annotation
                                       automatically
                         Extraction    generated               DAML annotated
        DAML
                         to DAML                               text or web pages
       Annotator
                         Translation


            Text or                                      DAML
           web pages     Text Extraction                 Ontologies


 Page 23                                                              JS01 June 4-6, 2001
Principals, Practice & Experience

 UBOT Architecture: COTS Components
    UML GUI
            Tau UML Suite (Telelogic)
    Specware (Kestrel Institute)
            supports ontology consistency checking via formal methods
            SNARK theorem prover (SRI)
    Text Extraction
            AeroText (LM M&DS)
               extracts entities (e.g. people, organizations, etc.) from natural language
               recognizes relationships between entities
                (e.g. [organization] hired [person] )
               developed for the U.S. Intelligence Community
               12 years experience with sophisticated linguistic processing
               many fielded applications
 Page 24                                                                     JS01 June 4-6, 2001
Principals, Practice & Experience

 UML GUI: Tau UML Suite




 Page 25                            JS01 June 4-6, 2001
Principals, Practice & Experience

 Text Extraction: AeroText
                                        Document
                                         Window
 Extraction
  Display




 Page 26                            JS01 June 4-6, 2001
Principals, Practice & Experience

 Automatic Annotation: AeroDAML




 Page 27                            JS01 June 4-6, 2001
Principals, Practice & Experience




                           Questions?




 Page 28                                JS01 June 4-6, 2001

				
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