How do we peer review data? New sustainable and effective models


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Authors
Cadwallader, Lauren 
McNeice, Kiera 
Eglen, Stephen 
Description

Materials relating to the fifth webinar of Cambridge Data Week 2020. Peer review is an area of open research that has received a growing amount of attention in the efforts to make it more transparent. However, the peer review process around data is still emerging despite the increase in data sharing. This session explores how peer review of data could be approached from both the perspective of a publisher and that of a researcher.

In a panel discussion with audience interaction, we explore three key areas:

Why should we review data? What are the benefits to the research community, researchers and journals?

What does it mean to conduct peer review of data? What types of data are being reviewed, beyond the ‘traditional’ spreadsheets of quantitative data? What can we learn from new models of data reviews?

Who is doing the work? How can we make the work of reviewing data sustainable, and the burden equitably shared? Do journals need a new pool of reviewers? What skills do reviewers need, and how do they acquire these?

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