An Ontology-based Approach to Context Modeling and Reasoning in Pervasive Computing

1. An Ontology-based Approach to Context Modeling and Reasoning in Pervasive Computing DejeneEjigu, Marian Scuturici, Lionel BrunieLaboratoire INSA de Lyon, France Fifth Annual IEEE International ConferencePervasive Computing and Communications Workshops (PerComW 07), 2007 Summarized and Presented by Seungseok KangIDS Lab.

2. Outline • Introduction • Related Works • Context Modeling • What is context? • Using reification in context modeling • The need for semantic context model • Ontology based context management model • Case study on reasoning • Conclusion and Future Work

3. Introduction • The emergence of pervasive computing environment • Context and context-awareness are the key components in pervasive computing • Pervasive environment • Dynamicity • Heterogeneity • Ubiquity • Goals • Propose and investigate ontology based semantically rich, reusable and scalable context management model • Support collaborative reasoning in a multi-domain pervasive context-aware application Conceptual framework of pervasiveness

4. Related Works • CoolTown • development of application specific context-aware systems • CoBra-ONT • Context model based on semantic web approach with context broker • CONON • Ontology for reasoning and representation • CSCP • Resource description framework for representation and manipulation of context data

5. Context Modeling • What is Context? • Computational entities should be able to adapt themselves to changing situations • Dey et al.’s definition of context • The most widely referenced definition • “Any information that can be used to characterize the situation of an entity. An entity is a user, a place, or a physical or computational object that is considered relevant to the interaction between a user and an application, including the user and application themselves.“ • Context Definition • Operation terms • Inherent characteristics of the entity • Interpretation of the operations involved on an entity

6. Context Modeling (cont.) • Hierarchy of context entities and relations • Primary characteristics of a context : Actor (subject) • Type and value of context is expressed by predicate and object • Ontology Representation • Basic RDF Triple <subject predicate object> • hierarchical classification of context • All descriptors have some properties to inherit from the root ContextEntity • Lower entities indicates context on the specific domain if application (instances)

7. Using Reification • Context modeling requires additional information • time, place, validity, claims, doubts, proofs, … • Extend the context model towards probabilistic models • RDF reification • Method to represent additional context attributes • Four properties used to model the original statement • Subject, predicate, object, type • Example • “Bob is located in the library”- “is reported by sensor #5”- “has accuracy of 88%”- “has occurred at 11:40 today” RDF data model on context reification

8. The Need for Semantic Context Model • Example • Need for a context model that describe concepts, concept hierarchies, relationships between concepts • Using OWL to define properties, relations, and axioms • Enhance the potential of semantic context reasoning • “if user1 is located in a roomN and user2 is also located in roomN then conclude that they are coLocatedWith each other or according to the above similarity definition they are together” a SELECT subjectFROM table.contextWHERE predicate=“isLocatedIn” AND object=“Room-305” ……Result?

9. Ontology Based Context Management Model • Generic Context Management (GCoM) Model • Context Ontology • semantics, concepts,relationships in thecontext data • Context Data • Instances of context • Context Related Rules • Derivation axioms thatare used by systems toreason out and derivedecisions about the actions that follow • explicit rules (by user) / implicit rules (by system itself) General Components of the GCoM model

10. Ontology Based Context Management Model (cont.) • Example : cell phone ringing tone management service • Student must have their cell phones set to non disturbing modes (automatically) during different activities • Attending lecture • Consultation with their professors • In libraries • Student need to have their phones automatically switched to silent or vibrating mode when they are engaged in activities • It must be switched back when they are engaged in none of activities • Student like to use a decent ringing tone when in the vicinity of the campus • They also like to use musical ringing tone when outside the campus

11. Ontology Based Context Management Model (cont.) Context representation for the scenario (RDF/XML)(Can be stored in any standard database format) Part of context ontology for the scenario (OWL)

12. Ontology Based Context Management Model (cont.) • Domain specific rules (using Jena) • For student’s explicit wishes in the scenario Rule representation for the scenario

13. Case Study on Reasoning • Context-aware service platform with GCoM model • Interface Manager • Manages a user interfaceand other modules • GCoM model • Provide the data necessary to provide proactive or reactivecontext-aware service • Rules • Plays an important role in the process of reasoning about context • Implicit rules (derived from the ontology) • Explicit rules (defined by user in the specific domain) GCoM in a context-aware platform

14. Case Study on Reasoning (cont.) • Context-aware Service • Provide the core context-aware services • Reasoning, decision making, action selecting • Supplementary Service • Types of service which use the information from context-aware service • Knowledge Discovery, Collaboration, Security, … • Revise: campus cell phone ringing tone management • Three GCoM element • OWL for context ontology (cellphone.owl) • RDF/XML for context data representation (cellphone.ctxt) • RDQL/SparQL for rule management and reasoning (cellphone.rules)

15. Conclusion • Propose the GCoM model based on ontology representation of context data, its semantics, context instances and rules • Rules are either derived or defined by user based on the requirement and policies • Breaking down of context in to semi-independent components is a unique contribution of GCoM • Context Instance, Context Semantics, Context Rules • GCoM make the context dynamic and reusable in a pervasive computing environment • Future work • Incorporate and use GCoM model with CoCA service platform • Evaluate the performance of proposed model and platform • Guarantee Scalability by separating relevant context data