Authors:
Mitchell G. Gillespie
1
;
Deborah A. Stacey
1
and
Stephen S. Crawford
2
Affiliations:
1
University of Guelph, Canada
;
2
University of Guelph and Chippewas of Nawash Unceded First Nation, Canada
Keyword(s):
Ontology-Driven Compositional System (ODCS), Ontology, System composition, User expectations, Fish population, Modeling.
Related
Ontology
Subjects/Areas/Topics:
Applications and Case-studies
;
Artificial Intelligence
;
Data Engineering
;
Decision Support Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Symbolic Systems
Abstract:
Ontology-Driven Compositional Systems (ODCSs) are designed to assist a user with semi- or fully automatic composition of a desired system. Current research with ODCSs has been conducted around the discovery and composition of web services and alternatively a bottom-up resource management approach to automatic system composition. This paper argues that current ODCSs do not truly satisfy user expectations as the semantic knowledge required to make proper discovery, decision-making and composition has not been fully represented. The authors introduce the beginning of their work of utilizing the inheritance of multiple ontologies to fully represent the functional, data, quality & trust, and execution of compositional units within an ODCS. Furthermore, a case study of fish population modeling is presented.