Extracting linked data from statistic spreadsheets

Tien-Duc Cao, I. Manolescu, Xavier Tannier
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引用次数: 17

Abstract

Statistic data is an important sub-category of open data; it is interesting for many applications, including but not limited to data journalism, as such data is typically of high quality, and reflects (under an aggregated form) important aspects of a society's life such as births, immigration, economy etc. However, such open data is often not published as Linked Open Data (LOD) limiting its usability. We provide a conceptual model for the open data comprised in statistics published by INSEE, the national French economic and societal statistics institute. Then, we describe a novel method for extracting RDF LOD, to populate an instance of this model. We used our method to produce RDF data out of 20k+ Excel spreadsheets, and our validation indicates a 91% rate of successful extraction.
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从统计电子表格中提取关联数据
统计数据是开放数据的一个重要子类;这对许多应用来说都很有趣,包括但不限于数据新闻,因为这些数据通常是高质量的,并且(以汇总形式)反映了一个社会生活的重要方面,如出生、移民、经济等。然而,这些开放数据通常不作为链接开放数据(LOD)发布,限制了其可用性。我们为法国国家经济和社会统计机构INSEE公布的统计数据中包含的开放数据提供了一个概念模型。然后,我们描述了一种提取RDF LOD的新方法,以填充该模型的实例。我们使用我们的方法从20k+ Excel电子表格中生成RDF数据,我们的验证表明成功提取的比率为91%。
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