DS - Spring 2006 Ontology & Pervasive Computing 1 ONTOLOGY & PERVASIVE COMPUTING Elham Paikari Distributed Systems – Spring 2006 Computer Engineering Department Sharif University Of Technology

DS - Spring 2006 Ontology & Pervasive Computing 2 Why do we use ontology?  To describe the semantics of the data (which we name as Meta-Data) Why do we describe the semantics?  In order to provide a uniform way to make different parties to understand each other Which data?  Any data (on the web, or in the existing legacy databases) Introduction

DS - Spring 2006 Ontology & Pervasive Computing 3 Formal definition on Ontology: Ontologies are knowledge bodies that provide a formal representation of a shared conceptualization of a particular domain. Recently ontologies have become increasingly common on WWW where they provide semantics of annotations in web pages There is growing evidence for the potential value of Semantic Web technology for Web Services and other open, distributed systems. Introduction

DS - Spring 2006 Ontology & Pervasive Computing 4 Ontology Engineering : Defining terms in the domain and relations among them Defining concepts in the domain (classes) Arranging the concepts in a hierarchy (subclass-super class hierarchy) Defining which attributes and properties (slots) classes can have and constraints on their values Defining individuals and filling in slot values What Is “Ontology Engineering”? determine scope consider reuse enumerate terms define classes define properties define constraints create instances

DS - Spring 2006 Ontology & Pervasive Computing 5 Domain-specific vocabulary Well-defined semantic structure Classes/concepts/types E.g., a class { Publication } represents all publications E.g., a class { Publication } can have subclasses { Newspaper }, { Journal } Instances/individuals/objects E.g., the newspaper Le Monde is an instance of the class { Newspaper } Properties/roles/slots Data E.g., the class { Publication } and its subclasses { Newspaper }, { Journal } have a data property { numberOfPages } Object E.g., the class { Publication } and its subclasses { Newspaper }, { Journal } have an object property { publishes } A Formal Definition

DS - Spring 2006 Ontology & Pervasive Computing 6 What they are good for Search Concept-based query: User uses own words, language Intelligent query expansion: “fishing vessels in China” expands to “fishing vessels in Asia” Consistency checking e.g., “Goods” has a property called “price” that has a value restriction of number Interoperability support Terms defined in expressive ontologies allow for mapping precisely how one term relates to another

DS - Spring 2006 Ontology & Pervasive Computing 7 Graphical notations Semantic networks Topic maps UML RDF Logic based Description Logics (e.g., OIL, DAML+OIL, OWL) Rules (e.g., RuleML, LP/Prolog) First Order Logic Ontology Languages

DS - Spring 2006 Ontology & Pervasive Computing 8 OWL (RDF/XML) Jane Smith An example ontology for profiling in OWL:

DS - Spring 2006 Ontology & Pervasive Computing 9 Physical environments saturated with computing and communication, yet gracefully integrated with human users. Distributed computing systems Large number of autonomous entities (or agents) Pervasive Computing Environments

DS - Spring 2006 Ontology & Pervasive Computing 10 Entities: devices, applications, services, databases, users or other kinds of agents. Various types of middleware (based on CORBA, Java RMI, SOAP, etc.) Enable communication between different entities. No facilities to ease semantic interoperability between the different entities. Pervasive Computing Environments

DS - Spring 2006 Ontology & Pervasive Computing 11 The ad hoc, and dynamic Nature late binding The user interface, available while on the go, is usually limited in modalities, bandwidth between users, and so on. Ontologies in the pervasive computing environment are more manageable compared to, for example, those for the Internet. Why ontology &pervasive computing

DS - Spring 2006 Ontology & Pervasive Computing 12 Ontologies for devices will be created by device manufacturers, which can put resources into their creation. Embodiments of devices with physical representations related to the particular location lead to simpler ontologies. You can have the same device in the next room or downstairs, and there is real reuse of ontologies enabled by natural boundaries in physical environments. On the other hand, people and companies on the Internet are under the constant pressure of differentiating from others because of the Internet’s universal connectivity (the very reason for its success). Why ontology &pervasive computing

DS - Spring 2006 Ontology & Pervasive Computing 13 Confront the development and deployment of Pervasive Computing Environments: Discovery and Matchmaking Inter-operability between different entities Context-awareness Three Major Issues

DS - Spring 2006 Ontology & Pervasive Computing 14 Registries to keep a real time state of the system A protocol for discovering the arrival and departure of mobile entities A registry with these protocols is termed a “Discovery Service” Standard schemas Policies, constraints, and relationships Flexible mechanism for exchanging descriptive information Discovery

DS - Spring 2006 Ontology & Pervasive Computing 15 using the Discovery Service to discover what entities are available what sets or combinations meet certain criteria Matchmaking

DS - Spring 2006 Ontology & Pervasive Computing 16 New entities The interaction Autonomous entities to interact need to know : What kinds of interfaces they support What protocols or commands they understand Humans need to understand: What various entities do The relationships between such entities It is essential for humans to form an accurate conceptual model of the environment: “They can interact with the environment easily.” Inter-operability

DS - Spring 2006 Ontology & Pervasive Computing 17 The various types of contextual information that can be used in the environment must be well- defined so that different entities have a common understanding of context. Also, there needs to be mechanisms for humans to specify how different applications and services should behave in different contexts. These mechanisms need to be based on well- defined structures of different types of context information. Context-Awareness

DS - Spring 2006 Ontology & Pervasive Computing 18 Checking to see if the descriptions of different entities are consistent with the axioms defined in the ontology. This also helps ensuring that certain security and safety constraints are met by the environment. Enabling semantic discovery of entities. users can gain a better understanding of the environment and how different pieces relate to each Other. Allowing both humans and automated agents to perform searches on different components easily Ontologies For

DS - Spring 2006 Ontology & Pervasive Computing 19 Both humans and automated agents to interact with different entities easily Allowing both humans and automated agents to specify rules for context-sensitive behavior of different entities easily Enabling new entities (which follow different ontologies) to interact with the system easily. Providing ways for ontology interoperability also allows different pervasive environments to interact with one another. Ontologies For

DS - Spring 2006 Ontology & Pervasive Computing 20 Ontologies for different entities Ontologies for context information Kinds of Ontologies in GAIA

DS - Spring 2006 Ontology & Pervasive Computing 21  Configuration management  Discovery and matchmaking  Human Interfaces  Interoperation of components  Context Sensitive behavior Ontology Server Tasks

DS - Spring 2006 Ontology & Pervasive Computing 22 Configuration Management  New entities, never before seen, may enter  Components need to automatically discover and collaborate with other components  Entities and components are heterogeneous and autonomous. Uses of Ontologies

DS - Spring 2006 Ontology & Pervasive Computing 23 Semantic Discovery and Matchmaking The Ontology Server performs the tasks of semantic discovery and matchmaking. It poses logical queries involving subsumption and classification of concepts Other entities in the environment query the Ontology Server to discover classes of components that meet their requirements. Uses of Ontologies

DS - Spring 2006 Ontology & Pervasive Computing 24 Improved Human Interfaces Ontologies can be used to make better user interfaces and allow these environments to interact with humans in a more intelligent way. “Ontology Explorer” Allows users to browse the ontology describing the environment. A user can search for: Different classes in the ontology Browse the results Get properties of the class Uses of Ontologies

DS - Spring 2006 Ontology & Pervasive Computing 25 Improved Inter-operability between entities The description of the properties of different classes of entities both users and other automated Agents interact with them more easily by performing searches on them or sending them various commands. This has proved to be one of the major advantages to using ontologies in a pervasive computing environment Uses of Ontologies

DS - Spring 2006 Ontology & Pervasive Computing 26 Context-Sensitive Behavior An ontology can improve Robustness Portability of context-aware applications. Different sensors different versions of services Localizations If the differences are terminological, an ontology may allow the rules to be “translated” and then work correctly in the new environment. Uses of Ontologies

DS - Spring 2006 Ontology & Pervasive Computing 27 Ontology Mapping The new ontology will add to the shared ontology using bridge concepts that relate classes and properties in the new ontology to existing classes and properties in the shared ontology. These bridge concepts are typically subsumption relations that define the new entity to be a subclass of an existing class of entities. For example, if a new kind of fingerprint recognizer is added to the system, the bridge concept may state that it is a subclass of “Authentication Devices”. Uses of Ontologies How should I use them? !!! ? ? ? ? ? ?? d c b a

DS - Spring 2006 Ontology & Pervasive Computing 28 A standard API for DAML+OIL (or, more likely, OWL [W3C, 2002b]) A standard interface for generic Knowledge Base services Future Software

DS - Spring 2006 Ontology & Pervasive Computing 29 “SOUPA” Standard Ontology for Ubiquitous and Pervasive Applications Nov In OWL UbiComp( From Existing Ontologies A Standard Ontology For Pervasive Computing

DS - Spring 2006 Ontology & Pervasive Computing 30 FOAF : People Profile, and Relationship DAML-Time : Time, and Scheduling RCC, OpenCyc : Description, Analysis Place and context MoGATU-BDI, COBRA-ONT : Display and Analysis of Knowledge Policy ontology (Rei) : High Level Rules, Access Control Standard Ontology From

DS - Spring 2006 Ontology & Pervasive Computing 31 Have Two Parts Core (For entity description) Extensions (For different Context) Adding Temporal Logic we have: Time Decision Making Standard Ontology

DS - Spring 2006 Ontology & Pervasive Computing 32 Adding tldatatype To RDF with these types: Active Next Previous Temporalformula Ontology For Pervasive Computing (sound.turn = = off) U ((cont.counter.active > cont.counter.previous) & (cont.counter.active< cont.counter.next))

DS - Spring 2006 Ontology & Pervasive Computing 33 [1] Harry Chen, Tim Finin, and Anupam Joshi, "An Ontology for Context- Aware Pervasive Computing Environments", Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, [2] Harry Chen ، Filip Perich ، Tim Finin ، Anupam Joshi, “SOUPA: Standard Ontology for Ubiquitous and Pervasive Applications”, University of Maryland, First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous'04), August 22 – 26, [3] Ryusuke Masuoka and Yannis Labrou, "Ontology-Enabled Pervasive Computing Applications", Fujitsu Laboratories of America, Published by the IEEE Computer Society, [4] Anand Ranganathan, et al., "Ontologies in a Pervasive Computing Environment, Content Areas: architectures, platforms, applications, semantic interoperability, semantic web services, role of context, environments", [5] Anand Ranganathan ، Robert E. McGrath, Roy H. Campbell, M. Dennis Mickunas, “Use of Ontologies in a Pervasive Computing Environment”, In The Knowledge Engineering Review, Vol 18:3, , Cambridge University Press, [6] Sven van der Meer and Nazim Agoulmine, "Ontology Based Policy Mobility for Pervasive Computing", Waterford Institute of Technology, Ireland, Declan O’Sullivan, David Lewis, Trinity College Dublin, Ireland, [7] References

DS - Spring 2006 Ontology & Pervasive Computing 34 Thanks