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Comparing closely related, semantically rich ontologies: The GoodOD Similarity Evaluator

Proceedings article published in 2012 by Niels Grewe, Daniel Schober ORCID, Martin Boeker
This paper is available in a repository.
This paper is available in a repository.

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Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
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Published version: policy unknown

Abstract

Objective To provide an integrated cross-platform ontology evalua-tion tool based on normalisation techniques and ontology similarity measures. Background Ontology similarity measures are extensively used in ontology matching applications but can also be applied to ontol-ogy evaluation scenarios (e.g. in ontology learning) when a 'gold standard' ontology is available against which similarity can be com-puted. Unfortunately, while there are software packages for similarity measurement available that are well suited for more terminologically oriented uses, there is no ready to use solution that copes well with the requirements of more formal ontologies, namely the reliance on top-level ontologies and the presence of semantically rich axiomatic class definitions. Methods We reviewed and applied several similarity measures for the appraisal of data collected in an ontology teaching experiment. We also optimised and applied ontology normalisation techniques to pre-process ontology artefacts in order to produce more consistent results. Results We implemented an advanced normalisation procedure to improve the usefulness of structural similarity measures in the pres-ence of rich class definitions and provide a highly configurable, ready to use tool for performing comparisons of individual ontologies or groups of ontologies. Conclusion Similarity measurements as established in the ontology alignment communities can also serve specific use-cases in ontology evaluation, but their application to semantically richer ontologies, as exemplified by many biomedical ontologies, requires special consid-erations to be taken into account. We therefore believe that providing an easily accessible tool for performing similarity measurement under these conditions is of considerable value to the biomedical ontology engineering community.