TWC data-gov corpus: incrementally generating linked government data from data.gov.
WWW(2010)
摘要
ABSTRACTThe 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 trade-off 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 mash-ups by declaratively reusing cross-dataset mappings which usually are hard-coded in applications.
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