context aware processing of ontologies in mobile environments
DESCRIPTION
Paper review of context aware processing of ontologiesTRANSCRIPT
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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
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AgendaAgendaOntologyMobileOntoDB projectSummary
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OntologyOntologyAn ontology is a controlled vocabulary of well defined terms with specified relationships between themcapable of interpretation by both computers and humans
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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
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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
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Motivation Motivation
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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.
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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
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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)
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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.
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OWL LP SQL OWL LP SQL
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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?
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SummarySummaryMeta Mapping of ontologies into logic
programs has◦ Higher expressivity◦ Better performance
Extended by context awareness of reasoning system◦ Architecture & open issues
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APPENDIXAPPENDIX
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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.
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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".
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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.
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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.