Barbara Gallina, Gergő László Steierhoffer, Thomas Young Olesen, Eszter Parajdi, Mike Aarup
{"title":"Towards an ontology for process compliance with the (machinery) legislations","authors":"Barbara Gallina, Gergő László Steierhoffer, Thomas Young Olesen, Eszter Parajdi, Mike Aarup","doi":"10.1002/smr.2728","DOIUrl":null,"url":null,"abstract":"Legislations impose requirements on the manufacturing of machinery. Typically, these requirements are interpreted and refined by (domain‐specific) technical committees and published in terms of standards. At the company level, these refined requirements are further interpreted, refined, and documented in terms of internal processes. Due to the proliferation of (interdependent) legislations and standards and the consequent increase of the cognitive complexity, at the company level, manual knowledge management is becoming more and more challenging and requires automated decision support. Despite the availability of approaches aimed at automating the decision support, no one offers a satisfactory solution. In this paper, we focus on knowledge management for process compliance and we propose a novel structured ontology. Our ontology aims at mastering (by dividing and conquering via tracing) the cognitive complexity of the compliance problem, when heterogeneous and sometimes geographically distributed knowledge‐driven organizational structures (legal department, standardization department, etc.) are involved and need to communicate. We also illustrate the potential usefulness of our proposed ontology in the context of pumps manufacturing and safety process compliance with the Machinery Directive and related harmonized standards including EN 809:1998+A1. Specifically, first, we identify the competencies that characterize departments and interdepartment interactions, then we formulate an initial set of competency questions that translate those identified competencies, then we show how the ontology can be exploited to retrieve the answers to the questions and how the answers can be exploited to build a justification for compliance. Precisely, we propose an argumentation pattern given in two different argumentation notations, and we show how it can be partly instantiated by exploiting the returned answers. The illustration also partly covers the compliance with the Machinery Regulation, expected to replace the Machinery Directive by January 2027. Finally, we sketch our intended future work.","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"17 1","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Software-Evolution and Process","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1002/smr.2728","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Legislations impose requirements on the manufacturing of machinery. Typically, these requirements are interpreted and refined by (domain‐specific) technical committees and published in terms of standards. At the company level, these refined requirements are further interpreted, refined, and documented in terms of internal processes. Due to the proliferation of (interdependent) legislations and standards and the consequent increase of the cognitive complexity, at the company level, manual knowledge management is becoming more and more challenging and requires automated decision support. Despite the availability of approaches aimed at automating the decision support, no one offers a satisfactory solution. In this paper, we focus on knowledge management for process compliance and we propose a novel structured ontology. Our ontology aims at mastering (by dividing and conquering via tracing) the cognitive complexity of the compliance problem, when heterogeneous and sometimes geographically distributed knowledge‐driven organizational structures (legal department, standardization department, etc.) are involved and need to communicate. We also illustrate the potential usefulness of our proposed ontology in the context of pumps manufacturing and safety process compliance with the Machinery Directive and related harmonized standards including EN 809:1998+A1. Specifically, first, we identify the competencies that characterize departments and interdepartment interactions, then we formulate an initial set of competency questions that translate those identified competencies, then we show how the ontology can be exploited to retrieve the answers to the questions and how the answers can be exploited to build a justification for compliance. Precisely, we propose an argumentation pattern given in two different argumentation notations, and we show how it can be partly instantiated by exploiting the returned answers. The illustration also partly covers the compliance with the Machinery Regulation, expected to replace the Machinery Directive by January 2027. Finally, we sketch our intended future work.