This document is a revision of the public working draft dated 1998-08-19 incorporating suggestions received in review comments and further deliberations of the W3C RDF Model and Syntax Working Group. With the publication of this draft, the RDF Model and Syntax Specification enters "last call." The last call period will end on October 23, 1998. Comments on this specification may be sent to www-rdf-comments@w3.org. The archive of public comments is available at http://www.w3.org/Archives/Public/www-rdf-comments. Significant changes from the previous draft are highlighted in Appendix E. While we do not anticipate substantial changes, we still caution that further changes are possible. Therefore while we encourage active implementation to test this specification we also recommend that only software that can be easily field-upgraded be implemented to this specification at this time. This is a W3C Working Draft for review by W3C members and other interested parties. Publication as a working draft does not imply endorsement by the W3C membership. The RDF Model and Syntax Working Group will not allow early implementation to constrain their ability to make changes to this specification prior to final release. This is a draft document and may be updated, replaced or obsoleted by other documents at any time. It is inappropriate to cite W3C Working Drafts as other than "work in progress". This work is part of the W3C Metadata Activity.

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the ‘Semantic Web, ’ for the idea of adding meaning — is only now emerging. ” 1 This characterization caused great confusion with respect to the relationships between the Semantic Web and the Web itself, as well as between the Semantic Web and some aspects of the so-called Web 2.0. Some wanted to reject the term “Web 3.0 ” as too business-oriented; others felt that the vision in the article was only part of the larger Semantic Web vision, and still others felt that, whatever it was called, the Semantic Web’s arrival in the Business section of The New York Times reflected an important coming of age.

? Novel/practical reasoning mechanisms? Graph metrics on multi-relational/semantic networks? Designing programming languages that exploit such structures AAAI Symposium on Technosocial Predictive Analytics – Stanford University, California – March 24, 2009 2Knowledge Representation and Reasoning • Knowledge representation: a model of a domain of discourse – structure. • Reasoning: an algorithm by which implicit knowledge is made explicit – process. Reasoner read/write

Communicated by Akihiro Fujiwara Sharing the Semantic Web data encoded in Resource Description Framework (RDF) triples from proprietary datasets scattered around the Internet, calls for efficient support from dis-tributed computing technologies. The highly dynamic ad-hoc settings that would

Specification (RDFS) is the foundation of the Semantic Web and an ontology representation language for database structures. Reification and anonymous resources are two of the more interesting features of RDFS, which is an important and advanced step toward natural language specification of data

. Generally, a multitude of tools is used for the management of a Web application life cycle. It is highly desirable to provide an exchange format for such tools to enable interoperability. This paper presents an eXtensible Web Modeling Framework (Xwmf), which applies the Resource Description

In this paper we propose an access control model for the Resource Description Framework (RDF). We argue that existing access control models, like the ones developed for securing eXtensible Markup Language (XML) documents, do not provide sufficient protection for RDF. Our model is based on RDF data

Abstract: The Resource Description Framework (RDF) is a standard developed by the World Wide Web Consortium (W3C) to facilitate the representation and ex-change of structured (meta-)data in the “Semantic Web”. While there is a large body of work dealing with inference on RDF, a concept

The Resource Description Framework (RDF) is providing the life sciences with new standards around data and knowledge management. The uptake in the life sciences is significantly higher than the uptake of the eXtensible Markup Language (XML) and even relational databases, as was recently shown