Ontology-Based Knowledge Representation for Self-governing Systems

Self-governing systems need a reliable set of semantics and a formal theoretic model in order to facilitate automated reasoning. We present an ontology-based knowledge representation that will use data from information models while preserving the semantics and the taxonomy of existing systems. This...

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Bibliographic Details
Published inLarge Scale Management of Distributed Systems pp. 74 - 85
Main Authors Lehtihet, Elyes, Strassner, John, Agoulmine, Nazim, Foghlú, Mícheál Ó
Format Book Chapter Conference Proceeding
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg 2006
Springer
SeriesLecture Notes in Computer Science
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Exact sciences and technology
Information systems. Data bases
Memory organisation. Data processing
Software
Speech and sound recognition and synthesis. Linguistics
Validation
Automated reasoning
Ontology
Taxonomy
Knowledge representation
Reuse
Knowledge base
Network management
Distributed system
Modeling
Formal semantics
Information use
Semantic web
Formal specification
Object constraint language
Object oriented
System representation
Data models
Shared memory
User need
Large scale system
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Summary:Self-governing systems need a reliable set of semantics and a formal theoretic model in order to facilitate automated reasoning. We present an ontology-based knowledge representation that will use data from information models while preserving the semantics and the taxonomy of existing systems. This will facilitate the decomposition and validation of high level goals by autonomous, self-governing components. Our solution reuses principles and standards from the Semantic Web and the OMG to precisely describe the managed entities and the shared objectives that these entities are trying to achieve by autonomously correlating their behavior. We describe how we created UML2, MOF, OCL and QVT ontologies, and we give a case study using the NGOSS Shared Information and Data model. We also set the requirements for integrating existing information models and domain ontologies into a unique knowledge base.
ISBN:3540476598
9783540476597
ISSN:0302-9743
1611-3349
DOI:10.1007/11907466_7