Semantic history towards modeling and publishing changes of online semantic data

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{{#vardefine:authoreditor|Jie Bao; Li Ding; Deborah L. McGuinness}}

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abstract: Effective revision tracking is important to maintain and use Semantic Web data for both publishers and readers. Information related to revisions in this setting often contains basic context information, semantic difference summary, and rationale summary. In this work, we present a general architecture for modeling and publishing revision history of social semantic Web data. This model has been implemented as an extension to an existing infrastructure, namely Semantic MediaWiki. We show a variety of applications that can be built using the framework, including provenance tracking, statistics, temporal reasoning and explanation.

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AbstractEffective revision tracking is important t Effective revision tracking is important to maintain and use Semantic Web data for both publishers and readers. Information related to revisions in this setting often contains basic context information, semantic difference summary, and rationale summary. In this work, we present a general architecture for modeling and publishing revision history of social semantic Web data. This model has been implemented as an extension to an existing infrastructure, namely Semantic MediaWiki. We show a variety of applications that can be built using the framework, including provenance tracking, statistics, temporal reasoning and explanation. stics, temporal reasoning and explanation.
AuthorJie Bao  +, Li Ding  +, and Deborah L. McGuinness  +
Bibtypeinproceedings  +
BooktitleProceedings of the 2nd Workshop on Social Data on the Web (SDoW2009)  +
Key2009semantic  +
PaperTW-2009-17.pdf  +
Paper urlhttp://tw.rpi.edu/portal/File:TW-2009-17.pdf  +
RelationInference web  +
SlidesTW-2009-17.ppt  +
TagProvenance  +, Semantic web  +, and Computer science  +
TitleSemantic History: Towards Modeling and Publishing Changes of Online Semantic Data  +
Tr idTW-2009-17  +
Year2009  +
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