An Ontology-based Approach to Context Modeling and Reasoning in Pervasive Computing Dejene Ejigu, Marian Scuturici, Lionel Brunie Laboratoire INSA de Lyon, France Fifth Annual IEEE International Conference Pervasive Computing and Communications Workshops (PerComW 07), 2007 Summarized and Presented by Seungseok Kang IDS Lab.

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

Conceptual framework of pervasiveness 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

Related Works CoolTown CoBra-ONT CONON CSCP 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

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

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)

RDF data model on context reification 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

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 subject FROM table.context WHERE predicate=“isLocatedIn” AND object=“Room-305” ……Result?

Ontology Based Context Management Model Generic Context Management (GCoM) Model Context Ontology semantics, concepts, relationships in the context data Context Data Instances of context Context Related Rules Derivation axioms that are used by systems to reason out and derive decisions about the actions that follow explicit rules (by user) / implicit rules (by system itself) General Components of the GCoM model

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

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

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

Case Study on Reasoning Context-aware service platform with GCoM model Interface Manager Manages a user interface and other modules GCoM model Provide the data necessary to provide proactive or reactive context-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

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)

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