Survey on common strategies of vocabulary reuse in linked open data modeling

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Abstract

The choice of which vocabulary to reuse when modeling and publishing Linked Open Data (LOD) is far from trivial. There is no study that investigates the different strategies of reusing vocabularies for LOD modeling and publishing. In this paper, we present the results of a survey with 79 participants that examines the most preferred vocabulary reuse strategies of LOD modeling. The participants, LOD publishers and practitioners, were asked to assess different vocabulary reuse strategies and explain their ranking decision. We found significant differences between the modeling strategies that range from reusing popular vocabularies, minimizing the number of vocabularies, and staying within one domain vocabulary. A very interesting insight is that the popularity in the meaning of how frequent a vocabulary is used in a data source is more important than how often individual classes and properties are used in the LOD cloud. Overall, the results of this survey help in better understanding the strategies how data engineers reuse vocabularies and may also be used to develop future vocabulary engineering tools. © 2014 Springer International Publishing.

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APA

Schaible, J., Gottron, T., & Scherp, A. (2014). Survey on common strategies of vocabulary reuse in linked open data modeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8465 LNCS, pp. 457–472). Springer Verlag. https://doi.org/10.1007/978-3-319-07443-6_31

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