Abstract
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 (offen DBpedia) that contain at most hundreds of millions of 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 with a small memory footprint. .is 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.
Original language | English |
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Title of host publication | Proceedings of the 13th International Conference on Semantic Systems, SEMANTiCS 2017 |
Publisher | Association for Computing Machinery |
Pages | 181-184 |
Number of pages | 4 |
Volume | 2017-September |
ISBN (Electronic) | 9781450352963 |
DOIs | |
Publication status | Published - 11 Sept 2017 |
Event | 13th International Conference on Semantic Systems, SEMANTiCS 2017 - Amsterdam, Netherlands Duration: 12 Sept 2017 → 13 Sept 2017 |
Conference
Conference | 13th International Conference on Semantic Systems, SEMANTiCS 2017 |
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Country/Territory | Netherlands |
City | Amsterdam |
Period | 12/09/17 → 13/09/17 |