Featuring news from Peer Review Week, help for smaller scientific societies with the transition to Plan S and recommendations by NIH to make data more FAIR

Focus on quality during Peer Review Week! via The Scholarly Kitchen

Now in its fifth year, Peer Review Week is the global celebration of the role that peer review plays in scholarly communication. This year, the focus was on ‘quality in peer review’. Topics included perspectives on what quality in peer review looks like, how journals can ensure high standards and whether this matters to the public. To hear from a range of voices around the world about quality in peer review, check out the Peer Review Week YouTube channel.

In this post, Director of Sense about Science, Tracey Brown OBE, explains the importance of peer review. Tracey’s organization has been involved with Peer Review Week since its launch, its core aim being to share the value of peer review with the public. Tracey explains that the quality of a publication, a grant application or an abstract is improved both indirectly and directly through peer review. Indirect improvement is achieved through the researcher knowing that their submission will be scrutinized during peer review, which urges them to constantly re-evaluate their own work, and direct improvement comes by incorporating feedback from the peer reviewers. And in an age of abundance of information and misinformation, the critical scrutiny of peer review is valuable in helping to choose what to read, trust, publish or fund. To educate the public about the importance of the peer review system, Sense about Science has published a handy guide called ‘I Don’t Know What to Believe’, explaining the peer review system, how the public can make sense of science stories, and what to consider valid and original.

Preparing for Plan S via Science

In last week’s Open Pharma weekly digest, we shared the release of a new report and toolkit to help learned societies and other publishers in transitioning to immediate open access and entering transformative agreements that are compliant with Plan S. This week, we reflect on why tools such as this one are important. Plan S, which requires researchers funded by participating organizations to publish their papers so that they are immediately free to read, has caused fear amongst small scientific societies relying heavily on subscription revenues that they might be ‘collateral damage’. The toolkit, released last week by the Society Publishers Accelerating Open Access and Plan S project, includes tips and contract templates that can be used to reach deals with libraries, which would eventually eliminate subscriptions while protecting revenue. As the public in the UK knows well, deal negotiations can be complex and require a great deal of time and resources that a small company would struggle to find. One way in which this project is helping is by arranging pilots that use the guidance; this will allow researchers served by library consortia to publish an unlimited number of open access articles in return for a set fee paid to societies. So far, five societies and four library consortia have committed in principle to test the transformative agreements.

NIH strategies for enhancing data sharing via US National Library of Medicine

The Findable, Accessible, Interoperable and Reusable (FAIR) data principles facilitate the discovery of and access to scientific data, and are also the principles that the National Institutes of Health (NIH) is aiming to apply to NIH-funded data, as outlined in its strategic plan for data science. The guest post by Susan Gregurick, Associate Director for Data Science at NIH, focuses on data sharing through domain-specific and generalist repositories. Susan explains that strengthening the data repository ecosystem would accelerate data-driven research and discovery. In the event that data do not fit with a domain-specific repository, generalist repositories (e.g. Figshare), which accept any data type or discipline, can be used. With a large data limit, Figshare complies with FAIR principles and allows all research outputs to be citable, shareable and discoverable.

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