Context-Aware Processing of Context-Aware Processing of Ontologies in Mobile Ontologies in Mobile EnvironmentsEnvironments

By : Gunther Specht and Timo WeithonerUniversity of Ulm89069 Ulm, Germany

AgendaAgendaOntologyMobileOntoDB projectSummary

OntologyOntologyAn ontology is a controlled vocabulary of well defined terms with specified relationships between themcapable of interpretation by both computers and humans

ReasonerReasonera reasoner, is a piece of software

able to infer logical consequences from a set of asserted facts or axiom

A logic allows the axiomatization of the domain information, and the drawing of conclusions from that information.

Syntax Semantics Logical inference = reasoning

MobileOntoDBMobileOntoDBGoal: develop a context-aware,

database based ontology reasoner for mobile devices

Limitations: mobile resources are restricted

Approach: “meta mapping”◦ Scale down the database reasoner to work

on mobile devices ◦ Add dynamic context awareness

Motivation Motivation

Context AwarenessContext AwarenessMobile devices know some context

◦ Location (GPS)◦ Time (Schedule)◦ People around (Bluetooth connection)

But our definition of context is broader◦ Absolute and relative location of the user◦ Time, date and even schedule of the user◦ Situation and current activity of the user◦ Availability of networks and network-services◦ Availability of persons (detected via Bluetooth) and

resources◦ Further sensor data: weather, health conditions, etc.

Representation of ContextRepresentation of ContextExtend the ontology language with

special elements to declare context◦ Drawback: extended reasoners would need

to be developedIntegrate context into ontologies using

existing language elements

Database supported Database supported Reasoning Reasoning Relational Reasoner based on 2 step

mapping mechanism◦First step: convert an ontology into a

logic program (OWL LP)◦Second step: convert logic program

into relational database like SQL (LP SQL)

OWL LPOWL LP OWL to LP can be achieved by a “Direct Mapping” or a

“Meta Mapping” approach Direct Mapping approach

◦ Intersection of DL with LP (called DLP) covering RDF schema and a subset of OWL

◦ Has scalability and representational issuesMeta Mapping Approach◦ Maps LP subset of OWL into a higher representational

level resulting in lower computational complexity and more representational flexibility.

OWL LP SQL OWL LP SQL

ArchitectureArchitectureBackend servers/Mobile devices both hold

part of ontologyHomogenous storage and reasoning

environment on server and mobile client

DBMS

Relational

Reasoner

Server

MobileDBMS

Relational

Reasoner

Mobile Device

MobileDBMS

Relational

Reasoner

Mobile Device

MobileDBMS

Relational

Reasoner

Mobile Device

Open Issues•Is there a way to delegate parts of the reasoning dynamically from a mobile device to a central reasoning server?•Transmission vs. replication?

SummarySummaryMeta Mapping of ontologies into logic

programs has◦ Higher expressivity◦ Better performance

Extended by context awareness of reasoning system◦ Architecture & open issues

APPENDIXAPPENDIX

OWLOWLA family of knowledge

representation languages for authoring ontologies endorsed by the World Wide Web Consortium. They are characterized by formal semantics and RDF/XML-based serializations for the Semantic Web. OWL has attracted both academic, medical and commercial interest.

RDFRDFResource Description Framework

(RDF) is a family of World Wide Web Consortium (W3C) specifications originally designed as a metadata data model. It has come to be used as a general method for conceptual description or modeling of information that is implemented in web resources, using a variety of syntax formats.

"The sky has the color blue" in RDF is as the triple: a subject denoting "the sky", a predicate denoting "has the color", and an object denoting "blue".

Description LogicDescription LogicDescription Logic, are decidable are decidable

fragments of First Order Logicfragments of First Order Logic. For a particular task, a logic is decidable if it is possible to design an algorithm that will terminate in a finite number of steps (i.e., the algorithm is guaranteed not to run forever).

provide a logical formalism for Ontologies and the Semantic Web.

Logic ProgramsLogic Programsa backwards reasoning theorem-prover

applied to declarative sentences in the form of implications:

If B1 and … and Bn then H treats the implications as goal-

reduction procedures:to show/solve H, show/solve B1 and …

and Bn. formalised in the Prolog notationH :- B1, …, Bn.