A semantic framework for enabling model integration for biorefining. (8th May 2017)

• Record Type: Journal Article
• Authors: Koo, Linsey; Trokanas, Nikolaos; Cecelja, Franjo
• Is Part Of: Computers & chemical engineering. Volume 100(2017)
• Page Start: 219
• Page End: 231
• Publication Date: 2017-05-08
• Subjects: Ontology engineering -- Model integration -- Computer aided process engineering (CAPE) -- Biorefining; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2017.02.004
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: We propose a semantic approach for establishing the interoperability between models and data. Introduction of input/output matching as a mean of integration based on the structure of domain ontology. The algorithm is implemented as a service. Demonstration of performance is achieved using a real-life biorefining modelling scenario. Abstract: This paper introduces a new paradigm for establishing a framework that enables interoperability between process models and datasets using ontology engineering. Semantics are used to model the knowledge in the domain of biorefining including both tacit and explicit knowledge, which supports registration and instantiation of the models and datasets. Semantic algorithms allow the formation of model integration through input/output matching based on semantic relevance between the models and datasets. In addition, partial matching is employed to facilitate flexibility to broaden the horizon to find opportunities in identifying an appropriate model and/or dataset. The proposed algorithm is implemented as a web service and demonstrated using a case study.