towards semantic methodologies for automatic regulatory compliance support
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.
regulatory compliance compliance management text analysis reasoning semantic annotation information extraction natural language processing ontology