Contextualized RDF Importing

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Citation: Bao, J., Ding, L., and McGuinness, D.L. 2010. Contextualized RDF Importing. In Proceedings of W3C Workshop on RDF Next Steps (June 26-27 2010June 26-27 2010June 26-27 2010, Palo Alto, CAPalo Alto, CA, USA).

Presented at the W3C Workshop on RDF Next Steps

Abstract:

RDF is a key enabling technology for linked data. However, currently RDF lacks a mechanism to connect data from different documents as well to address the contextual differences in these documents. We propose to introduce rdf:imports for context-aware integration of RDF documents.

History

DateCreated ByLink
July 19, 2011
13:18:56
Jie BaoDownload

Related Projects:

Inference Web Project LogoInference Web
Principal Investigator: Deborah L. McGuinness
Description: The Inference Web is a Semantic Web based knowledge provenance infrastructure that supports interoperable explanations of sources, assumptions, learned information, and answers as an enabler for trust. Provenance - if users (humans and agents) are to use and integrate data from unknown, uncertain, or multiple sources, they need provenance metadata for evaluation Interoperability - more systems are using varied sources and multiple information manipulation engines, thus increasing interoperability requirements Explanation/Justification - if information has been manipulated (i.e., by sound deduction or by heuristic processes), information manipulation trace information should be available Trust - if some sources are more trustworthy than others, trust ratings are desired The Inference Web consists of two important components: Proof Markup Language (PML) Ontology - Semantic Web based representation for exchanging explanations including provenance information - annotating the sources of knowledge justification information - annotating the steps for deriving the conclusions or executing workflows trust information - annotating trustworthiness assertions about knowledge and sources IW Toolkit - Web-based and standalone tools that facilitate human users to browse, debug, explain, and abstract the knowledge encoded in PML.

Related Research Areas:

Social Web
Lead Professor: Jim Hendler
Description: Social Web
Concepts: Semantic Web