Abstract
Ontology-Driven Compositional Systems (ODCSs) are designed to assist a user with semi- or fully automatic composition of a desired system utilizing previously implemented algorithms and/or software. Current research with ODCSs has been conducted around the discovery and composition of web services and a resource management approach. This chapter utilizes the collaboration with a Fish Population Modelling research group to argue that current ODCSs do not fully consider a users’ expectations of [a] his/her leverage and acquisition of knowledge from the ODCS, and [b] the trustworthy, high quality, and efficient performance of desired resultant systems. The authors support their argument by acknowledging that the current semantic frameworks have yet to fully represent the knowledge required to make proper discovery, decision-making, and composition. The authors introduce the beginning of their work of utilizing the inheritance of multiple ontologies to fully represent the function, data, execution, quality, trust, and timeline semantics of compositional units within an ODCS. Finally, a case study is utilized to illustrate how a more robust representation model will improve the satisfaction of the user’s expectations.
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Gillespie, M.G., Stacey, D.A., Crawford, S.S. (2013). Designing Ontology-Driven System Composition Processes to Satisfy User Expectations: A Case Study for Fish Population Modelling. In: Fred, A., Dietz, J.L.G., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2010. Communications in Computer and Information Science, vol 272. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29764-9_20
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