LegalRuleML : XML-based rules and norms

  1. (PDF, 624 KB)
  2. Get@NRC: LegalRuleML : XML-based rules and norms (Opens in a new window)
DOIResolve DOI:
AuthorSearch for: ; Search for: ; Search for: ; Search for: ; Search for: ; Search for:
TypeBook Chapter
Proceedings titleRule-Based Modeling and Computing on the Semantic Web : 5th International Symposium, RuleML 2011– America, Ft. Lauderdale, FL, Florida, USA, November 3-5, 2011. Proceedings
Series titleLecture Notes In Computer Science; Volume 7018
Conference5th International Symposium on Rules : Research Based and Industry Focused (RuleML 2011), November 3-5, 2011, Fort Lauderdale, Florida, USA
Pages298312; # of pages: 15
Subjectlegal rules; Legal XML Standards; semantic web; legal reasoning; LegalRuleML
AbstractLegal 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.
Publication date
PublisherSpringer Berlin Heidelberg
AffiliationNational Research Council Canada; NRC Institute for Information Technology
Peer reviewedYes
NPARC number19669782
Export citationExport as RIS
Report a correctionReport a correction
Record identifier9037f70f-cd1f-4cab-9ca1-36f4d952016d
Record created2012-03-20
Record modified2016-06-29
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)