Data2paper: Giving Researchers Credit for Their Data

被引:2
作者
Jefferies, Neil [1 ]
Murphy, Fiona [2 ]
Ranganathan, Anusha [3 ]
Murray, Hollydawn [4 ]
机构
[1] Univ Oxford, Bodleian Lib, Oxford OX2 0EW, England
[2] Univ Reading, Dept Meteorol, Reading RG6 6AS, Berks, England
[3] Digital Nest Ltd, Oxford OX1 3LE, England
[4] F1000Res, London W1T 4LB, England
关键词
data papers; publication; open data; credit;
D O I
10.3390/publications7020036
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
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.
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页数:6
相关论文
共 3 条
[1]  
Kratz John, 2014, F1000Res, V3, P94, DOI 10.12688/f1000research.3979.1
[2]   Data Papers - Peer Reviewed Publication of High Quality Data Sets [J].
Newman, Paul ;
Corke, Peter .
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2009, 28 (05) :587-587
[3]  
[The Royal Society's Rationale for a More Diverse Nuanced Set of Metrics], NUANC SET METR