The Legal-RDF Ontology. A Generic Model for Legal Documents

نویسنده

  • John McClure
چکیده

Legal-RDF.org publishes a practical ontology that models both the layout and content of a document and metadata about the document; these have been built using data models implicit within the HTML, XSL, and Dublin Core dialects. Directed Acyclic Graphs (DAGs) form the foundation of all models within the ontology, that is, DAGNode and DAGModel are the base classes for all other ontology classes, which include a restatement of RDF and OWL classes and properties as well as basic Kellog parts-of-speech. The ontology also represents an explicit semantic model used during its classifications: concrete classes are categorized as some element of a dramatic production, that is, as a subclass of Actor, Role, Scene, Prop, Theme, or Drama; this can be helpful during analyses of semantic perspective and context associated with resource definitions and attribute values. The LegalRDF ontology distinguishes between predicate verbs and predicate nouns in its models of a Statement to yield an intuitively appealing vocabulary that segregates attributes as past, present, future, or conditional, information. To facilitate development of generic tools, all data and object properties defined in the ontology’s models are categorized as a subproperty of one of the 15 Dublin Core properties; provenance data, with emphasis on an asOf timestamp, may be recorded for any attribute of a resource. Legal-RDF’s numeric properties derive from the ISO Systeme Internationale measurement systems; algebraic properties derive from XML Schema datatypes; language and currency designations are based upon relevant ISO standards; and time-zone designations are based on a review of local and regional standards (with some modifications necessary to eliminate collisions between the names of these properties and ISO standards). In addition to classes that represent quantities, classes are included that represent qualities that may be used to subtype or otherwise characterize instances.

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تاریخ انتشار 2007