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Ontological Anti-patterns in Aviation Safety Event Models

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Knowledge Engineering and Semantic Web (KESW 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 649))

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Abstract

Last years, there has been growing interest in developing high quality models to ensure interoperability of applications as well as proper understanding among a community. To improve productivity of model designers as well as to improve quality of resulting models, proper theoretical foundations and tool support is necessary. This paper discusses some types of conceptual modeling anti-patterns that lead to error- prone modeling decisions, and describes a reproducible solution to a general anti-pattern detection problem during conceptual design. Novel contribution of this paper is the definition of new ontological anti-patterns, we observed during our work in design and model ontologies in the domain of Aviation Safety. The approach is illustrated on models designed by means of OntoUML, an ontology-founded UML profile based on the Unified Foundational Ontology (UFO).

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Acknowledgments

This work was supported by grant No. GA 16-09713S Efficient Exploration of Linked Data Cloud of the Grant Agency of the Czech Republic and by grant No. SGS16/229/OHK3/3T/13 Supporting ontological data quality in information systems of the Czech Technical University in Prague.

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Authors and Affiliations

  1. Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic

    Jana Ahmad & Petr Křemen

Authors
  1. Jana Ahmad
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  2. Petr Křemen
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Corresponding author

Correspondence to Jana Ahmad .

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Editors and Affiliations

  1. Leipzig University , Leipzig, Germany

    Axel-Cyrille Ngonga Ngomo

  2. Czech Technical University in Prague , Praha, Czech Republic

    Petr Křemen

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Ahmad, J., Křemen, P. (2016). Ontological Anti-patterns in Aviation Safety Event Models. In: Ngonga Ngomo, AC., Křemen, P. (eds) Knowledge Engineering and Semantic Web. KESW 2016. Communications in Computer and Information Science, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-45880-9_2

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  • DOI: https://doi.org/10.1007/978-3-319-45880-9_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45879-3

  • Online ISBN: 978-3-319-45880-9

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