Rules and Ontology in Compliance Management
EDOC '07 Proceedings of the 11th IEEE International Enterprise Distributed Object Computing Conference
A static compliance-checking framework for business process models
IBM Systems Journal
Automating the Extraction of Rights and Obligations for Regulatory Compliance
ER '08 Proceedings of the 27th International Conference on Conceptual Modeling
Requirements and compliance in legal systems: a logic approach
RELAW '08 Proceedings of the 2008 Requirements Engineering and Law
Towards a framework for tracking legal compliance in healthcare
CAiSE'07 Proceedings of the 19th international conference on Advanced information systems engineering
Semantic-ART: a framework for semantic annotation of regulatory text
Proceedings of the fourth workshop on Exploiting semantic annotations in information retrieval
PIKM 2011: the 4th ACM workshop for Ph.D. students in information and knowledge management
Proceedings of the 20th ACM international conference on Information and knowledge management
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Businesses and organizations must comply with requirements and expectations such as regulations, policies, mandates and guidelines to meet public standards and avoid hefty penalties. Checking compliance manually is a laborious, extensive and error-prone process. The problems in the process are, to some extent, alleviated by using computerized compliance management systems. However, these systems are experiencing challenges in coping with the frequent changes and updates in the regulations. This paper describes our research on the use of semantic web technologies to support compliance management. In particular, we propose a methodology, RegCMatic that supports the management of the compliance system. Its originality lies on automating the extraction of regulatory information from regulatory texts, and mapping regulations to organizational internal processes. Our proposed methodology is applied to the Pharmaceutical industry, where regulatory information is extracted from the Eudralex EU regulation and modeled using a semantic formalism.