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Semantic Web in the Context Broker Architecture

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            Semantic Web in
     the Context Broker Architecture
     Harry Chen, Tim Finin, Anupam Joshi
        Univ. of Maryland, Baltimore County
                   PerCom 2004


         :: eBiquity Research Group :: CSEE :: UMBC ::
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                         Outline

     • Introduction
       • Issues in building context-aware systems
       • How Semantic Web languages can help
     • Background
       • The Semantic Web vision and ontologies
     • Context Broker Architecture (CoBrA)
       • Approach, design, and prototypes
     • Ongoing work & concluding remarks

           :: eBiquity Research Group :: CSEE :: UMBC ::
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     Computing Evolution …




      :: eBiquity Research Group :: CSEE :: UMBC ::
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     Pervasive Computing


                              Thank God!
                            PerCom is here…




     :: eBiquity Research Group :: CSEE :: UMBC ::
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     Intelligence is the Key


                               Sync.
                            Configuration?
                             Download
                           Too much work…
                              . Done.




     :: eBiquity Research Group :: CSEE :: UMBC ::
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            Context-Aware Systems

     • Context-awareness is a key aspect of the
       intelligent pervasive computing systems
     • Systems that can anticipate users’ needs and
       act in advance by “understanding” their
       context
       •   A system that knows I am the speaker
       •   A system that knows you are the audiences
       •   A system that knows we are in a conference
       •   …

              :: eBiquity Research Group :: CSEE :: UMBC ::
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                 What’s Context?

     • The situational conditions that are
       associated with a user
       • Location, room temperature, lighting
         conditions, noise level, social activities,
         user intentions, user beliefs, user roles,
         personal information, etc.




            :: eBiquity Research Group :: CSEE :: UMBC ::
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                      Related Work

     • Since the early 90’s, people have been
       interested in building context-aware systems
       •   Olivetti: Call forwarding & teleporting systems …
       •   Xerox PARC: Active map, PARC Tab …
       •   Georgia Tech.: Context toolkit, cyberguide …
       •   MIT: Office assistant, location-aware information
           delivery, intelligent room …
       •   UC Berkley: Context Fabric
       •   UIUC: Gaia
       •   HP Labs: Cooltown, CoolAgents …
       •   …
              :: eBiquity Research Group :: CSEE :: UMBC ::
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         The Shortcomings of the
            Previous Systems
     • Lacking an adequate representation for
       context modeling and reasoning
     • Individual agents are responsible for
       managing their own context knowledge
     • Users often have no control over the
       information that is acquired by the
       sensors

           :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                             ::
                 Research Issues

     • Context Modeling & Reasoning
       • How to represent context, so that it can be
         processed and reasoned by the computers
     • Knowledge Maintenance & Sharing
       • How to maintain consistent context knowledge
         and share that information with other systems
     • User Privacy Protection
       • How to let users to control the sharing and the use
         of their contextual information that is acquired by
         the hidden sensors


            :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                           ::
       Our Research Contributions

     • CoBrA: a broker-centric agent architecture
       for supporting pervasive context-aware
       systems
       • Using SW languages to define ontologies for
         context modeling and reasoning
       • Using logic inference to interpret context and to
         detect and resolve inconsistent knowledge
       • Allowing users to defined policies to control the
         use of their contextual information


            :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                         ::
            Other Contributions

     • EasyMeeting: a smart meeting room
       prototype that exploits CoBrA
       • Providing relevant services and information
         to meeting participants based on their
         situational needs
       • Allowing users to control the use and the
         sharing their location and social context



           :: eBiquity Research Group :: CSEE :: UMBC ::
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     Semantic Web & Ontologies




       :: eBiquity Research Group :: CSEE :: UMBC ::
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          About the Semantic Web

     • An extension to the present World Wide Web.
     • The focus is on enabling computing machines
       to be able to reason about web information in
       addition to display web information.
       • NOTE: displaying information does not necessarily
         require “deep” understanding of the information.
       • NOTE: in order to reason about information often
         requires “deep” understanding of the information.



            :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                                                   ::
        The Current Web
         (adopted from Eric Miller’s presentation http://www.w3.org/2004/Talks/0120-semweb-umich/)

     Resource:
         Identified by URI’s
         Untyped
     Links:
         “href”, “src” …
         non-descriptive

     Users:
        Exciting world - semantics
        of resource, however, gleaned
        from content
     Machine:
        Very little information available -
        significance of the links only evident from
        the context around the anchor


                      :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                                                    ::
         The Semantic Web
          (adopted from Eric Miller’s presentation http://www.w3.org/2004/Talks/0120-semweb-umich/)

     Resource:
         Globally identified by URI’s
         or locally scoped (blank)
         Extensible
         Relational
     Links:
         Identified by URI’s
         Extensible
         Relational

     Users:
        Even more exciting world, richer
        user experience
     Machine:
        More processable information
        is available (Data Web)
                       :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                          ::
     The Semantic Web Layer Cake
 “The Semantic Web will globalize KR,
 just as the WWW globalize hypertext”
 -- Tim Berners-Lee




                                we are
                                 here




            :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                           ::
           Semantic Web Ontologies

     • Formally, an ontology is an explicit
       specification of a conceptualization.
     • For the developers, building ontologies
       is about defining shared vocabularies
       and associated semantic relations
       •   SonyEricsson T68i is a type of cellphone
       •   All SonyEricsson T68i supports Bluetooth
       •   Harry has a SonyEricsson T68i device
       •   => Harry’s cellphone supports Bluetooth.
             :: eBiquity Research Group :: CSEE :: UMBC ::
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        Semantic Web Languages
             http://www.w3.org/2001/sw/

     • KR languages for defining ontologies
     • W3C Recommendations
       • RDF/RDFS -- represents information as N-
         Triples (subject, predicate, object);
         supports basic class-subclass & properties.
       • OWL (Web Ontology Language) -- adds
         more vocab. for describing classes and
         properties, cardinality, equality, XML
         datatypes, enumerations etc.

           :: eBiquity Research Group :: CSEE :: UMBC ::
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     OWL? Ontologies? But where?


                                    Pervasive
                                   computing is
                                      great!




         :: eBiquity Research Group :: CSEE :: UMBC ::
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              How does OWL Help?
                                 ontology
                                language           service
             context                              description
              model                                 lang.
                               { PerCom }

           meta lang                                    Interop
            (policy)                                   language
                               XSLT/XML
                                friendly

     OWL provided a uniformed language which met many needs
     in developing a complex pervasive computing system.
               :: eBiquity Research Group :: CSEE :: UMBC ::
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     Context Broker Architecture
              (CoBrA)




       :: eBiquity Research Group :: CSEE :: UMBC ::
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         Context Broker Architecture

                    Semantic                     Pervasive
                      Web                        Computing


                                  CoBrA




                               Software Agents

     CoBrA not CORBA!

             :: eBiquity Research Group :: CSEE :: UMBC ::
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     A Bird’s Eye View of CoBrA




       :: eBiquity Research Group :: CSEE :: UMBC ::
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          Key Features of CoBrA

     • Using OWL to define ontologies for
       context modeling and reasoning
     • Taking a rule based approach to
       interpret and reason about context
     • Using a policy language and engine to
       control the sharing of user context



           :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                                  ::
          An EasyMeeting Scenario

       Alice enters a         Alice “beams” her       The broker builds
     conference room          policy to the broker    the context model
                                                                              Web
                                             B                   B


     The broker detects          Policy says,             Policy says,
      Alice’s presence       “can share with any     “inform my personal
                             agents in the room”     agent of my location”
      B                                                 .. isLocatedIn ..
                              A
                                                      B                       A



                :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                            ::
           An EasyMeeting Scenario
      The broker tells her     Her agent informs        The broker informs
     location to her agent      the broker of her     the subscribed agents
                               role and intentions
                      A                +                B



     The projector agent      The projector agent      The projector agent
      wants to help Alice     asks slide show info.     sets up the slides

                                              B



                 :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                 ::
        Research Work in CoBrA

                             Context
                            Reasoner


      CoBrA                                            Privacy
     Ontologies                                       Protection




                           EasyMeeting
                            Prototype

           :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                       ::
     The CoBrA Ontology (v0.4)




            http://daml.umbc.edu/ontologies/cobra/0.4/

       :: eBiquity Research Group :: CSEE :: UMBC ::
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      Example 1: Location Inference

     • Goal: reason about a person’s location
       using the available sensing information.

     => Step 1: define a domain spatial ontology




           :: eBiquity Research Group :: CSEE :: UMBC ::
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     A Simple UMBC Ontology




      :: eBiquity Research Group :: CSEE :: UMBC ::
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                Location Inference
     Assume the broker is told that Harry is located in RM-201A




              :: eBiquity Research Group :: CSEE :: UMBC ::
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               Location Inference
     A: the used spatial relations are
     “rdfs:subProeprtyOf” the “inRegion” property

     B: “inRegion” is of type “Transitive Property”


     Based on A & B => …



             :: eBiquity Research Group :: CSEE :: UMBC ::
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       Location Inference




     :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                 ::
 Example 2: Spotting a Sensor Error
     Premise (static knowledge):
        R210 rdf:type AtomicPlace.
        ParkingLot-B rdf:type AtomicPlace.

     Premise (dynamic knowledge):
        Harry isLocatedIn R210.
        Harry isLocatedIn ParkingLot-B.

     Premise (domain knowledge):
        No person can be located in two different AtomicPlace at
        the same time.

     Conclusion: There is an error in the knowledge base.
               :: eBiquity Research Group :: CSEE :: UMBC ::
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                Context Reasoner

     Jena OWL/RDFS
                                                          Sensing
        Reasoner
                                                        Information

                              KB
                            (MySQL)
                                                        Context
       JESS Rule                                       Knowledge
         Engine

                       Context Broker

             :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                                       ::
             EasyMeeting Prototype #1
                                                                               Room ECS201
        CWM              N-Triple + Jena + RDQL    MySQL
     Tomcat Server

                                                           N-Triple + Jena + RDQL

     Context information (FIPA + OWL-XML)

                                                  Broker
                                                              Harry’s Policy    HTTP
                                                   JADE                         Server
        BT Sensor
            JADE
                                   The URL of Harry’s Policy (FIPA+N3)




                     :: eBiquity Research Group :: CSEE :: UMBC ::
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     EasyMeeting Prototype #2




       :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                   ::




         Work in Progress




     :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                         ::
      Things that I’m working on…

     • Enhancing the broker’s reasoning
     • Implementing a policy-based privacy
       protection mechanism
     • Building an Eclipse Plug-in for
       monitoring the “brain” of the broker
     • Working with other researchers to
       define a shared ontology for supporting
       PerCom applications.

           :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                          ::
        Enhancing the Reasoner;
        Adding Privacy Protection
     • Using an assumption-based reasoner
       (called Theorist) to support default and
       abductive reasoning
       • Tries to explain the observed sensing
         information by making hypotheses
         (abduction), and then predicts users’ future
         actions (defaults)
     • Using the Rei policy language & engine
       to support privacy protection

            :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                  ::
        Privacy Policy Use Case (1)
     • The speaker doesn’t want others to know the specific
       room that he is in, but does want others to know that
       he is present on the school campus
     • He defines the following policies:
        • Can share my location with a granularity > ~1 km radius
     • The broker:
        •   isLocated(US) => Yes!
        •   isLocated(Maryland) => Yes!
        •   isLocated(BaltimoreCounty) => Yes!
        •   isLocated(UMBC) => Yes!
        •   isLocated(ITE-RM-201A) => I don’t know…



               :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                          ::
       Privacy Policy Use Case (2)

     • The problem of inference!
       • Knowing your phone + white pages => I
         know where you live
       • Knowing your email address (.mil, .gov) =>
         I know you works for the government
     • The broker models the inference
       capability of other agents
       • mayKnow(X, homeAdd(Y)) :- know(X,phoneNum(Y))


            :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                                          ::
           CoBrA Eclipse Viewer (CEV)




                                   Inspired by the Java Spider application
                                   http://www.javaspider.org

     For exploring the knowledge and user policies that are stored in the
     Context Broker; for monitoring the broker’s reasoning process.
                  :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                         ::
      Building a Standard Ontology
      for Supporting PerCom Apps.
     • Standard Ontology for Ubiquitous
       and Pervasive Application (SOUPA)
       • Semantic Web in UbiComp SIG
       • http://pervasive.semanticweb.org/
     • The bigger goal of SW-UbiComp SIG
       • Bring together SW+PerCom researchers
       • Exploring the use of ontologies in PerCom


           :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                   ::




               Conclusions




     :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                         ::
        Semantic Web for PerCom

     • Semantic Web languages & ontologies
       can facilitate knowledge sharing,
       context reasoning, and user privacy
       protection in a PerCom environment
     • CoBrA is a new pervasive context-
       aware architecture that exploits the
       Semantic Web technologies


           :: eBiquity Research Group :: CSEE :: UMBC ::
::                                                         ::
                     Questions?

     • CoBrA (ontologies, CEV, source code)
       • http://cobra.umbc.edu
     • SW-UbiComp SIG
       • http://pervasive.semanticweb.org/
     • PerCom news & development
       • http://www.ebiquity.org/
     • Harry Chen
       • Google “Harry Chen”

           :: eBiquity Research Group :: CSEE :: UMBC ::

				
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