Legal texts are the foundational resource where to discover rules and norms that feed into different concrete (often XML-based) Web applications. Legislative documents provide general norms and specific procedural rules for eGovernment and eCommerce environments, while contracts specify the conditions of services and business rules (e.g. service level agreements for cloud computing), and judgments provide information about the legal argumentation and interpretation of norms to concrete case-law. Such legal knowledge is an important source that should be detected, properly modeled and expressively represented in order to capture all the domain particularities. This paper provides an extension of RuleML called LegalRuleML for fostering the characteristics of legal knowledge and to permit its full usage in legal reasoning and in the business rule domain. LegalRuleML encourages the effective exchange and sharing of such semantic information between legal documents, business rules, and software applications. © 2011 Springer-Verlag.
CITATION STYLE
Palmirani, M., Governatori, G., Rotolo, A., Tabet, S., Boley, H., & Paschke, A. (2011). LegalRuleML: XML-based rules and norms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7018 LNCS, pp. 298–312). https://doi.org/10.1007/978-3-642-24908-2_30
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