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Dataset reuse

An analysis of references in community discussions, publications and data
 
: Endris, K.M.; Giménez-García, J.M.; Thakkar, H.; Demidova, E.; Zimmermann, A.; Lange, C.; Simperl, E.

:

Association for Computing Machinery -ACM-:
K-CAP 2017. Proceedings of the Knowledge Capture Conference : Austin, TX, USA, December 04 - 06, 2017
New York: ACM, 2017
ISBN: 978-1-4503-5553-7
Art.5
International Conference on Knowledge Capture (K-CAP) <9, 2017, Austin/Tex.>
Englisch
Konferenzbeitrag
Fraunhofer IAIS ()

Abstract
Following the Linked Data principlesmeans maximising the reusability of data over the Web. Reuse of datasets can become apparent when datasets are linked to from other datasets, and referred in scientific articles or community discussions. It can thus be measured, similarly to citations of papers. In this paper we propose dataset reuse metrics and use these metrics to analyse indications of dataset reuse in different communication channels within a scientific community. In particular we consider mailing lists and publications in the Semantic Web community and their correlation with data interlinking. Our results demonstrate that indications of dataset reuse across different communication channels and reuse in terms of data interlinking are positively correlated.

: http://publica.fraunhofer.de/dokumente/N-502463.html