(397h) Reusing Ontologies in the Domain of Process Systems Engineering

Authors: 
Cecelja, F., University of Surrey
Trokanas, N., University of Surrey

The number of ontologies available today, more than 10,000 as identified by dedicated search engines[1], is a good indicator of the progress made so far. Ontologies are developed for and used in several applications ranging from knowledge representation and semantic search up to data integration and web service discovery (Cheung, Cheung & Kwok 2012)(Trokanas, Cecelja & Raafat 2013, Raafat et al. 2013b)(Raafat et al. 2013a). Much of recent ontology development efforts have been reported in the domain of Process Systems Engineering.(Trokanas et al. , Cecelja et al. 2013, Muñoz et al. 2012).

It is the fact that ontologies are by definition conceptualisations that are supposed to be shared and reused (Gruber 1993, Gruber 1995). Ontology reuse is a practical and useful approach for knowledge engineers. It has the potential to reduce the cost of developing ontology from scratch, as well as promote interoperability among applications. In addition, many of the existing ontologies cover similar or overlapping domains. Ontology reuse is also part of many of existing frameworks and established methodologies (Noy, McGuinness 2001, López et al. 1999) for ontology development. However, by reviewing the literature (Bock et al. 2010, Brandt et al. 2008, Fernandes et al. 2011, Giménez et al. 2008), it became apparent that ontology reuse is a seldom occurring task. Researchers have identified a lack in robust and pragmatic methods for evaluating and identifying ontologies for reuse.

This paper presents a metric for the evaluation of ontologies for reuse. The metric  account for ontology metadata such as the datatypes, external resources, terminology and languages used for modelling. It also accounts for structural characteristics of ontologies such as size, breadth and width of the evaluated ontologies. All the available information is translated into vectors which are consequently compared. The resulting similarity scores for each aspect are aggregated and normalised into a single metric ranging between [0,1]. The metric has been tested and verified using experiments for the development of an ontology for the domain of Industrial Symbiosis.

The effort has been partly funded by the LIFE+ initiative (LIFE 09 ENV/GR/000300) and EPSRC, which authors acknowledge.

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