What does Dataset Reuse tell us about Quality?

Abstract : Following the Linked Data principles means maximising the reusability of data over the Web. A strong reason for reusing a dataset is that it is considered useful for some application. Considering the broad definition of data quality as \fitness for use", the question arises whether quality of linked datasets and their actual reuse correlate, or, in other words, whether certain quality characteristics can be optimised to increase the potential reuse of the datasets. Reuse of datasets becomes apparent when datasets are referred to from other datasets, papers, or discussions within the community. It can thus be measured, similarly to citations of papers. Many other aspects of Linked Data quality have also been defined in a measurable way, i.e. as quality metrics. In this paper we present metrics to quantify dataset reuse in a scientific community and investigate their correlation with the quality metrics discussed in the literature.
Type de document :
Pré-publication, Document de travail
2016
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https://hal-emse.ccsd.cnrs.fr/emse-01317206
Contributeur : Florent Breuil <>
Soumis le : mercredi 18 mai 2016 - 11:16:35
Dernière modification le : dimanche 15 octobre 2017 - 22:44:06

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  • HAL Id : emse-01317206, version 1

Citation

Kemele M. Endris, José-M. Giménez-Garcıa, Harsh Thakkar, Elena Demidova, Christoph Lange, et al.. What does Dataset Reuse tell us about Quality?. 2016. 〈emse-01317206〉

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