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Ruben Verborgh

Machine-Interpretable Dataset and Service Descriptions for Heterogeneous Data Access and Retrieval

Anastasia Dimou, Ruben Verborgh, Miel Vander Sande, Erik Mannens, and Rik Van de Walle

The RDF data model allows the description of domain-level knowledge that is understandable by both humans and machines. RDF data can be derived from different source formats and diverse access points, ranging from databases or files in CSV format to data retrieved from Web APIs in JSON, Web Services in XML or any other speciality formats. To this end, vocabularies such as RML were introduced to uniformly define how data in multiple heterogeneous sources is mapped to the RDF data model, independently of their original format. This approach results in mapping definitions that are machine-processable and interoperable. However, the way in which this data is accessed and retrieved still remains hard-coded, as corresponding descriptions are often not available or not taken into account. In this paper, we introduce an approach that takes advantage of widely-accepted vocabularies, originally used to advertise services or datasets, such as Hydra or DCAT, to define how to access Web-based or other data sources. Consequently, the generation of RDF representations is facilitated, as the description of the interaction models with the original data remains independent, interoperable and granular.

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Published in 2015 in Proceedings of the 11th International Conference on Semantic Systems.

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Cite this article easily using its BibTeX entry: 

@inproceedings{dimou_semantics_2015,
  author = {Dimou, Anastasia and Verborgh, Ruben and Vander Sande, Miel and Mannens, Erik and Van de Walle, Rik},
  booktitle = {Proceedings of the 11th International Conference on Semantic Systems},
  title = {Machine-Interpretable Dataset and Service Descriptions for Heterogeneous Data Access and Retrieval},
  year = 2015,
  month = sep,
  pages = {145--152},
  doi = {10.1145/2814864.2814873},
  isbn = {978-1-4503-3462-4},
  url = {https://dl.acm.org/authorize?N20635},
}

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ACM
Anastasia Dimou, Ruben Verborgh, Miel Vander Sande, Erik Mannens, and Rik Van de Walle. 2015. Machine-Interpretable Dataset and Service Descriptions for Heterogeneous Data Access and Retrieval. In Proceedings of the 11th International Conference on Semantic Systems, 145–152.
APA
Dimou, A., Verborgh, R., Vander Sande, M., Mannens, E., & Van de Walle, R. (2015). Machine-Interpretable Dataset and Service Descriptions for Heterogeneous Data Access and Retrieval. Proceedings of the 11th International Conference on Semantic Systems, 145–152.
IEEE
A. Dimou, R. Verborgh, M. Vander Sande, E. Mannens, and R. Van de Walle, “Machine-Interpretable Dataset and Service Descriptions for Heterogeneous Data Access and Retrieval,” in Proceedings of the 11th International Conference on Semantic Systems, 2015, pp. 145–152.
LNCS
Dimou, A., Verborgh, R., Vander Sande, M., Mannens, E., Van de Walle, R.: Machine-Interpretable Dataset and Service Descriptions for Heterogeneous Data Access and Retrieval. In: Proceedings of the 11th International Conference on Semantic Systems. pp. 145–152 (2015).
MLA
Dimou, Anastasia, et al. “Machine-Interpretable Dataset and Service Descriptions for Heterogeneous Data Access and Retrieval.” Proceedings of the 11th International Conference on Semantic Systems, 2015, pp. 145–52.

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