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Open AccessArticle

Data2paper: Giving Researchers Credit for Their Data

Bodleian Libraries, University of Oxford, Oxford OX2 0EW, UK
Department of Meteorology, University of Reading, Reading RG6 6AS, UK
Digital Nest Ltd., Oxford OX1 3LE, UK
F1000Research, London W1T 4LB, UK
Author to whom correspondence should be addressed.
Publications 2019, 7(2), 36;
Received: 1 March 2019 / Revised: 31 March 2019 / Accepted: 23 May 2019 / Published: 27 May 2019
(This article belongs to the Special Issue Selected Papers from Open Repositories 2018)
Initially funded as part of the Jisc Data Spring Initiative, a team of stakeholders (publishers, data repository managers, coders) has developed a simple workflow to streamline data paper submission. Metadata about a dataset in a data repository is combined with ORCID metadata about the author to automate and thus greatly reduce the friction of the submission process. Funders are becoming more interested in good data management practice, and institutions are developing repositories to hold the data outputs of their researchers, reducing the individual burden of data archiving. However, to date only a subset of the data produced is associated with publications and thus reliably archived, shared and re-used. This represents a loss of knowledge, leading to the repetition of research (especially in the case of negative observations) and wastes resources. It is laborious for time-poor researchers to fully describe their data via an associated article to maximise its utility to others, and there is little incentive for them to do so. Filling out diverse submission forms, for the repository and journal(s), makes things even lengthier. The app makes the process of associating and publishing data with a detailed description easier, with corresponding citation potential and credit benefits. View Full-Text
Keywords: data papers; publication; open data; credit data papers; publication; open data; credit
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Jefferies, N.; Murphy, F.; Ranganathan, A.; Murray, H. Data2paper: Giving Researchers Credit for Their Data. Publications 2019, 7, 36.

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