Abstract
Linkitup is a Web-based dashboard for enrichment of research output published via industry grade data repository services. It takes metadata entered through Figshare.com and tries to find equivalent terms, categories, persons or entities on the Linked Data cloud and several Web 2.0 services. It extracts references from publications, and tries to find the corresponding Digital Object Identifier (DOI). Linkitup feeds the enriched metadata back as links to the original article in the repository, but also builds a RDF representation of the metadata that can be downloaded separately, or published as research output in its own right. In this paper, we compare Linkitup to the standard workflow of publishing linked data, and show that it significantly lowers the threshold for publishing linked research data.
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Notes
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See http://databib.org for a comprehensive listing.
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See also, http://www.neuinfo.org/ and http://data.nature.com.
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The Open Annotation model is defined by the W3C Open Annotation community group, and is subject to change. Linkitup uses the community draft of February 2013, http://www.openannotation.org/spec/core/20130208/index.html.
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Pubby is a standard front end for triple stores, see http://github.com/cygri/Pubby.
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voiD: vocabulary of interlinked datasets, see http://www.w3.org/TR/void/.
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This publication was supported by the Dutch national program COMMIT.
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Hoekstra, R., Groth, P., Charlaganov, M. (2014). Linkitup: Semantic Publishing of Research Data. In: Presutti, V., et al. Semantic Web Evaluation Challenge. SemWebEval 2014. Communications in Computer and Information Science, vol 475. Springer, Cham. https://doi.org/10.1007/978-3-319-12024-9_12
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DOI: https://doi.org/10.1007/978-3-319-12024-9_12
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