Business process compliance with regulations has been a topic of many research areas in Computer Science such as Requirements Engineering (RE), Artificial Intelligence (AI), Logic and Natural Language Processing (NLP). This work aims to provide a systematic way of establishing and managing compliance to assist decision-making and reporting. Despite many notable advances, few systems deal adequately with legal interpretation and modeling norms in an expressive way that is well-integrated with business modeling practices. In this paper, we bring together two leading systems, Legal-URN and Eunomos, for a comprehensive compliance management solution.

Integrating legal-URN and eunomos: Towards a comprehensive compliance management solution

Boella G.;Humphreys L.;
2014-01-01

Abstract

Business process compliance with regulations has been a topic of many research areas in Computer Science such as Requirements Engineering (RE), Artificial Intelligence (AI), Logic and Natural Language Processing (NLP). This work aims to provide a systematic way of establishing and managing compliance to assist decision-making and reporting. Despite many notable advances, few systems deal adequately with legal interpretation and modeling norms in an expressive way that is well-integrated with business modeling practices. In this paper, we bring together two leading systems, Legal-URN and Eunomos, for a comprehensive compliance management solution.
2014
Inglese
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Esperti anonimi
Springer Verlag
berlin
GERMANIA
8929
130
144
15
978-3-662-45959-1
978-3-662-45960-7
Compliance; Legal interpretation; Requirements engineering
4 – prodotto già presente in altro archivio Open Access (arXiv, REPEC…)
Boella G.; Tosatto S.C.; Ghanavati S.; Hulstijn J.; Humphreys L.; Muthuri R.; Rifaut A.; Van Der Torre L.
8
info:eu-repo/semantics/bookPart
02-CAPITOLO DI LIBRO::02A-Contributo in volume
268
none
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1762581
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