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A Proposed Ontology Evaluation Tool to Assist Ontology Engineers in Selecting Ontologies During the Reuse Phase

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Knowledge Graphs and Semantic Web (KGSWC 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 15459))

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Abstract

European data spaces are increasingly promoting interoperability among systems by the use of shared vocabularies and standardized data models. Ontologies, which provide structured vocabularies to uniformly interpret data, are crucial for achieving this interoperability. One essential step in ontology development is the reuse of existing ontologies. However, in the last decade, many efforts have been spent to develop ontologies that, in some cases, cover the same domain. Thus, selecting the most suitable one for reuse is becoming a challenging task for ontology engineers. To address this, we propose a tool that assists ontology engineers in evaluating and selecting ontologies based on various criteria, including structural features, lexical coverage, fairness, and maturity. This tool offers a comprehensive scoring system to guide decision-making during the reuse phase, ensuring efficient ontology integration. It will be validated through feedback from domain experts and applied to develop a unified semantic data model for energy data spaces.

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Notes

  1. 1.

    http://www.lov4iot.appspot.com/?p=lov4iot-energy.

  2. 2.

    https://github.com/Nushrat-Jahan/OntoReuse.

  3. 3.

    https://www.datamuse.com/api/.

  4. 4.

    SEAS Photovoltaic Ontology v1.0.

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Acknowledgement

This work is funded by the European Union’s Horizon Europe innovation action program under grant agreement no [101069287] (OMEGA-X). https://omega-x.eu/.

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Correspondence to Lina Nachabe .

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Nachabe, L., Jahan, N. (2025). A Proposed Ontology Evaluation Tool to Assist Ontology Engineers in Selecting Ontologies During the Reuse Phase. In: Tiwari, S., Villazón-Terrazas, B., Ortiz-Rodríguez, F., Sahri, S. (eds) Knowledge Graphs and Semantic Web. KGSWC 2024. Lecture Notes in Computer Science, vol 15459. Springer, Cham. https://doi.org/10.1007/978-3-031-81221-7_21

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  • DOI: https://doi.org/10.1007/978-3-031-81221-7_21

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