Authors:
H. Hlomani
;
M. G. Gillespie
;
D. Kotowski
and
D. A. Stacey
Affiliation:
University of Guelph, Canada
Keyword(s):
Ontologies, Ontology capture, Ontology evaluation, Knowledge engineering, Knowledge identification, BioSTORM, Context, Adaptability, Knowledge base.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Engineering
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Symbolic Systems
Abstract:
With the advent of such platforms as Service Oriented Architecture (SOA) and the open source community came the possibility of accessing free software/services. These may be in the form of web services, coded algorithms, legacy systems, etc. Users are able to define workflows through the combination of these software components with the aide of systems known as Ontology Driven Compositional Systems (ODCS). These systems have ontologies as their fundamental components that provide the knowledge bases that provide the rich descriptions of the ODCS components. Since these ontologies underlie ODCS, greater efforts must be spent in the engineering of these artifacts. We have thus proposed a knowledge identification framework that can be used as a guide within ontology engineering methodologies to perform such tasks as ontology capture and evaluation. In this paper we demonstrate the usage of this framework in a case study to evaluate the ontologies defined in the BioSTORM project. We do t
his by using a checklist (founded on the knowledge identification framework) through which we can evaluate the adaptability of the context of an ontology.
(More)