Following the Linked Data principles means 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.
%0 Conference Paper
%1 endris2017dataset
%A Endris, Kemele M.
%A Giménez-García, José M.
%A Thakkar, Harsh
%A Demidova, Elena
%A Zimmermann, Antoine
%A Lange, Christoph
%A Simperl, Elena
%B Proceedings of the Ninth International Conference on Knowledge Capture (K-CAP 2017)
%D 2017
%K data4urbanmobility myown wdaqua
%T Dataset Reuse: An Analysis of References in Community Discussions, Publications and Data
%X Following the Linked Data principles means 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.
@inproceedings{endris2017dataset,
abstract = {Following the Linked Data principles means 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. },
added-at = {2017-10-28T23:20:20.000+0200},
author = {Endris, Kemele M. and Giménez-García, José M. and Thakkar, Harsh and Demidova, Elena and Zimmermann, Antoine and Lange, Christoph and Simperl, Elena},
biburl = {https://www.bibsonomy.org/bibtex/2ff483f5baf5ed18fe6732038a4d7cbd0/demidova},
booktitle = {Proceedings of the Ninth International Conference on Knowledge Capture (K-CAP 2017)},
interhash = {23769239699d8dd5e33266f19e5cf657},
intrahash = {ff483f5baf5ed18fe6732038a4d7cbd0},
keywords = {data4urbanmobility myown wdaqua},
timestamp = {2017-12-18T11:07:12.000+0100},
title = {Dataset Reuse: An Analysis of References in Community Discussions, Publications and Data},
year = 2017
}