LOD-a-lot: A Single-File Enabler for Data Science

Wouter Beek, Javier D. Fernández, and Ruben Verborgh

Published in 2017 in Proceedings of the 13^th International Conference on Semantic Systems.

Many data scientists make use of Linked Open Data (LOD) as a huge interconnected knowledge base represented in RDF. However, the distributed nature of the information and the lack of a scalable approach to manage and consume such Big Semantic Data makes it difficult and expensive to conduct large-scale studies. As a consequence, most scientists restrict their analyses to one or two datasets (often DBpedia) that contain – at most – hundreds of millions of RDF triples. LOD-a-lot is a dataset that integrates a large portion (over 28 billion triples) of the LOD Cloud into a single ready-to-consume file that can be easily downloaded, shared and queried, locally or online, with a small memory footprint. This paper shows there exists a wide collection of Data Science use cases that can be performed over such a LOD-a-lot file. For these use cases LOD-a-lot significantly reduces the cost and complexity of conducting Data Science.

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Keywords:

• HDT
• data science
• data access
• Linked Data
• RDF
• DBpedia

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Cite this article easily using its BibTeX entry:

@inproceedings{beek_semantics_2017,
  author = {Beek, Wouter and Fern\'andez, Javier D. and Verborgh, Ruben},
  title = {{LOD-a-lot:} A Single-File Enabler for Data Science},
  booktitle = {Proceedings of the 13th International Conference on Semantic Systems},
  year = 2017,
}

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ACM

Wouter Beek, Javier D. Fernández, and Ruben Verborgh. 2017. LOD-a-lot: A Single-File Enabler for Data Science. In Proceedings of the 13^th International Conference on Semantic Systems.

APA

Beek, W., Fernández, J. D., & Verborgh, R. (2017). LOD-a-lot: A Single-File Enabler for Data Science. Proceedings of the 13^th International Conference on Semantic Systems.

IEEE

W. Beek, J. D. Fernández, and R. Verborgh, “LOD-a-lot: A Single-File Enabler for Data Science,” in Proceedings of the 13^th International Conference on Semantic Systems, 2017.

LNCS

Beek, W., Fernández, J.D., Verborgh, R.: LOD-a-lot: A Single-File Enabler for Data Science. In: Proceedings of the 13^th International Conference on Semantic Systems (2017).

MLA

Beek, Wouter, et al. “LOD-a-Lot: A Single-File Enabler for Data Science.” Proceedings of the 13^th International Conference on Semantic Systems, 2017.