Graph integration of structured, semistructured and unstructured data for data journalism

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

arXiv · 2012.08830

Graph integration of structured, semistructured and unstructured data for data journalism

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

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Abstract

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.

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Angelos-Christos Anadiotis, Oana Balalau, Catarina Conceicao, Helena Galhardas, Mhd Yamen Haddad, Ioana Manolescu, Tayeb Merabti, Jingmao You. 2020-12-16. Graph integration of structured, semistructured and unstructured data for data journalism. https://arxiv.org/abs/2012.08830

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