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Mapping diverse data to RDF in practice

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2018) 11136 LNCS 441-457
DOI: 10.1007/978-3-030-00671-6_26
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Abstract

Converting data from diverse data sources to custom RDF datasets often faces several practical challenges related with the need to restructure and transform the source data. Existing RDF mapping languages assume that the resulting datasets mostly preserve the structure of the original data. In this paper, we present real cases that highlight the limitations of existing languages, and describe D2RML, a transformation-oriented RDF mapping language which addresses such practical needs by incorporating a programming flavor in the mapping process.

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Chortaras, A., & Stamou, G. (2018). Mapping diverse data to RDF in practice. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11136 LNCS, pp. 441–457). Springer Verlag. https://doi.org/10.1007/978-3-030-00671-6_26

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