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Webinar: Ensuring your data policies are up to date and cover the FAIR principles

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posted on 2019-07-15, 16:40 authored by Dan ValenDan Valen, Iain HrynaszkiewiczIain Hrynaszkiewicz, Caroline Sutton, Alan HyndmanAlan Hyndman
There is an increasing need for publishers to make the data associated with journal publications openly available in a human and machine-readable, FAIR (findable, accessible, interoperable, and reusable) manner. Incorporating data sharing and publishing into the scholarly communication workflow has produced a number of challenges, ranging from technical to cultural.

Creating and implementing a data policy that incorporates the nuances of data publishing - and cultures and practices of peer-reviewed publications - is a first step in enacting and enforcing good data-sharing practice.

But, as a scholarly publisher, society or editor, where do you start? How do you ensure all of your broad research areas are considered? And how do you ensure your policy does not clash with existing funder and institutional policies? How do you ensure your policy promotes good practice but is practical and implementable in the real world?

Luckily, a working group at the Research Data Alliance (https://rd-alliance.org/) surveyed the academic publisher data policy landscape and consulted with a wide range of stakeholders to create a journal research data policy framework intended to work for all journals and publishers. It was published as a preprint in June 2019. https://figshare.com/articles/Developing_a_research_data_policy_framework_for_all_journals_and_publishers/8223365/1

In this webinar, Iain Hrynaszkiewicz from Springer Nature, lead author on the paper, will discuss the work that went into producing the publication and what the findings may mean for journals and publishers wishing to introduce or enhance research data policies. Joining Iain are Caroline Sutton from Taylor & Francis who recently implemented a data policy and Dan Valen from Figshare, talking about how Figshare functionality allows for the many dimensions of implementing a data policy.

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