Abstract

Data “publication” seeks to appropriate the prestige of authorship in the peer-reviewed literature to reward researchers who create useful and well-documented datasets. The scholarly communication community has embraced data publication as an incentive to document and share data. But, numerous new and ongoing experiments in implementation have not yet resolved what a data publication should be, when data should be peer-reviewed, or how data peer review should work. While researchers have been surveyed extensively regarding data management and sharing, their perceptions and expectations of data publication are largely unknown. To bring this important yet neglected perspective into the conversation, we surveyed ∼ 250 researchers across the sciences and social sciences– asking what expectations“data publication” raises and what features would be useful to evaluate the trustworthiness, evaluate the impact, and enhance the prestige of a data publication. We found that researcher expectations of data publication center on availability, generally through an open database or repository. Few respondents expected published data to be peer-reviewed, but peer-reviewed data enjoyed much greater trust and prestige. The importance of adequate metadata was acknowledged, in that almost all respondents expected data peer review to include evaluation of the data’s documentation. Formal citation in the reference list was affirmed by most respondents as the proper way to credit dataset creators. Citation count was viewed as the most useful measure of impact, but download count was seen as nearly as valuable. These results offer practical guidance for data publishers seeking to meet researcher expectations and enhance the value of published data.

Highlights

  • Data sharingIn 1985– almost 30 years ago– Stephen Ceci surveyed 847 scientists and concluded “it is clear that scientists in all fields endorse the principle of data sharing as a desirable norm of science” [1]

  • As data publication takes shape, the problem can be reduced by solidification of community norms around data use, increased prestige for dataset creators, and better adoption of formal data citation. The results of this survey offer some practical guidance for data publishers seeking to meet researcher expectations and enhance the value of datasets

  • The research and scholarly communication communities agree that formal citation is the way to credit a dataset creator, and a number of steps can be taken to encourage this practice

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Summary

Introduction

In 1985– almost 30 years ago– Stephen Ceci surveyed 847 scientists and concluded “it is clear that scientists in all fields endorse the principle of data sharing as a desirable norm of science” [1] This endorsement has not weakened over the decades; more than 65% of faculty at California Polytechnic State University (Cal Poly) affirmed the importance of data sharing in 2010 [2], as did 94% of the researchers in the United Kingdom (UK) surveyed by the Expert Advisor. We asked a number of questions to assess engagement and familiarity with data sharing and publication (Fig. 1) Respondents rated their familiarity with three US federal government policies related to data sharing and availability. The much older National Institutes of Health (NIH) data sharing policy [41] was enacted 11 years ago, but only four biologists (5%) claimed to know all the details, fewer than the 18 (24%) who had never heard of it

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