Verification of safety rules using nlp

Coen van Gulijk, Violeta Holmes

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A key step in the design of digitally enabled safety systems is the development of an Enterprise Architecture model (EA). The design of EA models tends to be a complex job that is usually performed by IT specialists that are not trained in safety. Very often, these EA models contain safety rules that are not well understood by IT specialists but they are of key importance for the safe implementation of the digital solutions. As part of safety directives, safety experts have to verify whether there are any safety issues in the EA model. This particular aspect of enterprise architecture verification is a manual process that is laborious and prone to error. This work investigates whether standard Natural Language Processing techniques (NLP) can help in the verification of safety rules within an enterprise architecture model. This paper demonstrates that this kind of verification is potentially very powerful but cannot be used on its own; ontological taxonomies are probably required as well.

Original languageEnglish
Title of host publicationProceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference
EditorsPiero Baraldi, Francesco Di Maio, Enrico Zio
PublisherResearch Publishing
Pages1255-1260
Number of pages6
ISBN (Print)9789811485930
DOIs
Publication statusPublished - 1 Nov 2020
Event30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM15 2020 - Venice, Italy
Duration: 1 Nov 20205 Nov 2020

Conference

Conference30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM15 2020
CountryItaly
CityVenice
Period1/11/205/11/20

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