The SemaDrift Protégé plugin to measure semantic drift in ontologies: Lessons learned

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Abstract

Semantic drift is an active research field, which aims to identify and measure changes in ontologies across time and versions. Yet, only few practical methods have emerged that are directly applicable to Semantic Web constructs, while the lack of relevant applications and tools is even greater. This paper presents the findings, current limitations and lessons learned throughout the development and the application of a novel software tool, developed in the context of the PERICLES FP7 project, which integrates currently investigated methods, such as text and structural similarity, into the popular ontology authoring platform, Protégé. The graphical user interface provides knowledge engineers and domain experts with access to methods and results without prior programming knowledge. Its applicability and usefulness are validated through two proof-ofconcept scenarios in the domains of Web Services and Digital Preservation; especially the latter is a field where such long-term insights are crucial.

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Stavropoulos, T. G., Andreadis, S., Kontopoulos, E., Riga, M., Mitzias, P., & Kompatsiaris, I. (2017). The SemaDrift Protégé plugin to measure semantic drift in ontologies: Lessons learned. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10180 LNAI, pp. 29–39). Springer Verlag. https://doi.org/10.1007/978-3-319-58694-6_3

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