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TWC data-gov corpus: incrementally generating linked government data from data.gov

11 years 7 months ago
TWC data-gov corpus: incrementally generating linked government data from data.gov
The Open Government Directive is making US government data available via websites such as Data.gov for public access. In this paper, we present a Semantic Web based approach that incrementally generates Linked Government Data (LGD) for the US government. In focusing on the tradeoff between high quality LGD generation (requiring non-trivial human expert input) and massive LGD generation (requiring low human processing cost), our work is highlighted by the following features: (i) supporting low-cost and extensible LGD publishing for massive government data; (ii) using Social Semantic Web (Web3.0) technologies to incrementally enhance published LGD via crowdsourcing, and (iii) facilitating mashups by declaratively reusing cross-dataset mappings which usually are hardcoded in applications. Categories and Subject Descriptors H.4.m [Information Systems]: Miscellaneous Keywords Linked Government Data, Social Semantic Web, Data.gov
Li Ding, Dominic DiFranzo, Alvaro Graves, James Mi
Added 14 May 2010
Updated 14 May 2010
Type Conference
Year 2010
Where WWW
Authors Li Ding, Dominic DiFranzo, Alvaro Graves, James Michaelis, Xian Li, Deborah L. McGuinness, James A. Hendler
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