Merging and enriching DCAT feeds to improve discoverability of datasets
- Author
- Pieter Heyvaert (UGent) , Pieter Colpaert (UGent) , Ruben Verborgh (UGent) , Erik Mannens (UGent) and Rik Van de Walle (UGent)
- Organization
- Abstract
- Data Catalog Vocabulary (DCAT) is a W3C specification to describe datasets published on the Web. However, these catalogs are not easily discoverable based on a user's needs. In this paper, we introduce the Node.js module 'dcat-merger' which allows a user agent to download and semantically merge different DCAT feeds from the Web into one DCAT feed, which can be republished. Merging the input feeds is followed by enriching them. Besides determining the subjects of the datasets, using DBpedia Spotlight, two extensions were built: one categorizes the datasets according to a taxonomy, and the other adds spatial properties to the datasets. These extensions require the use of information available in DBpedia's SPARQL endpoint. However, public SPARQL endpoints often suffer from low availability, its Triple Pattern Fragments alternative is used. However, the need for DCAT Merger sparks the discussion for more high level functionality to improve a catalog's discoverability.
- Keywords
- Linked open data, Open data, Triple pattern fragments, DCAT, Data publishing, Smart cities
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-7035179
- MLA
- Heyvaert, Pieter, et al. “Merging and Enriching DCAT Feeds to Improve Discoverability of Datasets.” Lecture Notes in Computer Science, vol. 9341, Springer International Publishing, 2015, pp. 67–71, doi:10.1007/978-3-319-25639-9_13.
- APA
- Heyvaert, P., Colpaert, P., Verborgh, R., Mannens, E., & Van de Walle, R. (2015). Merging and enriching DCAT feeds to improve discoverability of datasets. Lecture Notes in Computer Science, 9341, 67–71. https://doi.org/10.1007/978-3-319-25639-9_13
- Chicago author-date
- Heyvaert, Pieter, Pieter Colpaert, Ruben Verborgh, Erik Mannens, and Rik Van de Walle. 2015. “Merging and Enriching DCAT Feeds to Improve Discoverability of Datasets.” In Lecture Notes in Computer Science, 9341:67–71. Portoroz, Slovenia: Springer International Publishing. https://doi.org/10.1007/978-3-319-25639-9_13.
- Chicago author-date (all authors)
- Heyvaert, Pieter, Pieter Colpaert, Ruben Verborgh, Erik Mannens, and Rik Van de Walle. 2015. “Merging and Enriching DCAT Feeds to Improve Discoverability of Datasets.” In Lecture Notes in Computer Science, 9341:67–71. Portoroz, Slovenia: Springer International Publishing. doi:10.1007/978-3-319-25639-9_13.
- Vancouver
- 1.Heyvaert P, Colpaert P, Verborgh R, Mannens E, Van de Walle R. Merging and enriching DCAT feeds to improve discoverability of datasets. In: Lecture Notes in Computer Science. Portoroz, Slovenia: Springer International Publishing; 2015. p. 67–71.
- IEEE
- [1]P. Heyvaert, P. Colpaert, R. Verborgh, E. Mannens, and R. Van de Walle, “Merging and enriching DCAT feeds to improve discoverability of datasets,” in Lecture Notes in Computer Science, Portoroz, Slovenia, 2015, vol. 9341, pp. 67–71.
@inproceedings{7035179,
abstract = {{Data Catalog Vocabulary (DCAT) is a W3C specification to describe datasets published on the Web. However, these catalogs are not easily discoverable based on a user's needs. In this paper, we introduce the Node.js module 'dcat-merger' which allows a user agent to download and semantically merge different DCAT feeds from the Web into one DCAT feed, which can be republished. Merging the input feeds is followed by enriching them. Besides determining the subjects of the datasets, using DBpedia Spotlight, two extensions were built: one categorizes the datasets according to a taxonomy, and the other adds spatial properties to the datasets. These extensions require the use of information available in DBpedia's SPARQL endpoint. However, public SPARQL endpoints often suffer from low availability, its Triple Pattern Fragments alternative is used. However, the need for DCAT Merger sparks the discussion for more high level functionality to improve a catalog's discoverability.}},
author = {{Heyvaert, Pieter and Colpaert, Pieter and Verborgh, Ruben and Mannens, Erik and Van de Walle, Rik}},
booktitle = {{Lecture Notes in Computer Science}},
isbn = {{978-3-319-25638-2}},
issn = {{0302-9743}},
keywords = {{Linked open data,Open data,Triple pattern fragments,DCAT,Data publishing,Smart cities}},
language = {{eng}},
location = {{Portoroz, Slovenia}},
pages = {{67--71}},
publisher = {{Springer International Publishing}},
title = {{Merging and enriching DCAT feeds to improve discoverability of datasets}},
url = {{http://doi.org/10.1007/978-3-319-25639-9_13}},
volume = {{9341}},
year = {{2015}},
}
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