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Representation of Safety Standards with Semantic Technologies Used in Industrial Environments

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Computer Safety, Reliability, and Security (SAFECOMP 2017)

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Abstract

Understanding and following safety standards with their text can be difficult. Ambiguity and inconsistency, among other issues, can easily arise. As a solution, several authors argue for the explicit representation of the standards with models, which can be created with semantic technologies such as ontologies. However, this possibility has received little attention. The few authors that have addressed it have also only dealt with a subset of safety standard aspects and have used technologies not usually applied for critical systems engineering. As a first step towards addressing these issues, this position paper presents our initial work on the representation of safety standards with Knowledge Manager, a tool used in industrial environments that exploits semantic technologies to manage domain information. The proposal also builds on prior work on the specification of safety compliance needs with a holistic generic metamodel. We describe how to use Knowledge Manager to specify the concepts and relationships of the metamodel for a given safety standard, and discuss the application and benefits of the corresponding representation.

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Acknowledgments

The research leading to this paper has received funding from the AMASS project (H2020-ECSEL no. 692474; Spain’s MINECO ref. PCIN-2015-262).

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Correspondence to Jose Luis de la Vara .

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de la Vara, J.L., Gómez, Á., Gallego, E., Génova, G., Fraga, A. (2017). Representation of Safety Standards with Semantic Technologies Used in Industrial Environments. In: Tonetta, S., Schoitsch, E., Bitsch, F. (eds) Computer Safety, Reliability, and Security . SAFECOMP 2017. Lecture Notes in Computer Science(), vol 10489. Springer, Cham. https://doi.org/10.1007/978-3-319-66284-8_22

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  • DOI: https://doi.org/10.1007/978-3-319-66284-8_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66283-1

  • Online ISBN: 978-3-319-66284-8

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