Processing linked open data cubes

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Abstract

A significant part of open data provided by governments and international organizations concerns statistics such as demographics and economic indicators. The real value, however, of open statistical data will unveil from performing analytics on top of combined datasets from disparate sources. Linked data provide the most promising technological paradigm to enable such analytics across the Web. Currently, however, relevant processes and tools do not fully exploit the distinctive characteristics of statistical data. The aim of this paper is to present a process that enables publishing statistical raw data as linked data, combining statistics from multiple sources, and exploiting them in data analytics and visualizations. Moreover, the capability of existing software tools to support the vision of linked statistical data analytics is evaluated. We anticipate that the proposed process will contribute to the development of a roadmap for future research and development in the area.

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Tambouris, E., Kalampokis, E., & Tarabanis, K. (2015). Processing linked open data cubes. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9248, pp. 130–143). Springer Verlag. https://doi.org/10.1007/978-3-319-22479-4_10

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