arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2012.08830cs.DBcs.AI
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Graph integration of structured, semistructured and unstructured data for data journalism

École Polytechnique, Institut Polytechnique de Paris(巴黎理工学院综合理工学院);EPFL(洛桑联邦理工学院);Inria, Institut Polytechnique de Paris(法国国家信息与自动化研究所,巴黎理工学院);INESC-ID(里斯本系统与计算机工程研究所);IST, Univ. Lisboa(里斯本大学高等技术学院)

Angelos-Christos Anadiotis, Oana Balalau, Catarina Conceicao, Helena Galhardas, Mhd Yamen Haddad, Ioana Manolescu, Tayeb Merabti, Jingmao You

英文摘要:

Digital data is a gold mine for modern journalism. However, datasets which interest journalists are extremely heterogeneous, ranging from highly structured (relational databases), semi-structured (JSON, XML, HTML), graphs (e.g., RDF), and text. Journalists (and other classes of users lacking advanced IT expertise, such as most non-governmental-organizations, or small public administrations) need to be able to make sense of such heterogeneous corpora, even if they lack the ability to define and deploy custom extract-transform-load workflows, especially for dynamically varying sets of data sources. We describe a complete approach for integrating dynamic sets of heterogeneous datasets along the lines described above: the challenges we faced to make such graphs useful, allow their integration to scale, and the solutions we proposed for these problems. Our approach is implemented within the ConnectionLens system; we validate it through a set of experiments.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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