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Cambridge Data Week 2020 day 1: Who are the winners and losers of good data practices?
Cambridge Data Week 2020 was an event run by the Office of Scholarly Communication at Cambridge University Libraries from 23–27 November 2020. In a series of talks, panel discussions and interactive Q&A sessions, researchers, funders, publishers and other stakeholders explored and debated different approaches to research data management. This blog is part of a series summarising each event. The rest of the blogs comprising this series are as follows:Cambridge Data Week day 2 blog Cambridge Data Week day 3 blog Cambridge Data Week day 4 blog Cambridge Data Week day 5 blog Introduction The first day of Cambridge Data Week 2020 kicked off with a tantalisingly open question: who are…
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Cambridge Data Week 2020 day 2: Who is reusing data? Successes and future trends?
Cambridge Data Week 2020 was an event run by the Office of Scholarly Communication at Cambridge University Libraries from 23–27 November 2020. In a series of talks, panel discussions and interactive Q&A sessions, researchers, funders, publishers and other stakeholders explored and debated different approaches to research data management. This blog is part of a series summarising each event. The rest of the blogs comprising this series are as follows:Cambridge Data Week day 1 blogCambridge Data Week day 3 blogCambridge Data Week day 4 blogCambridge Data Week day 5 blog Introduction Reuse of data is the final element of the FAIR principles and has long been argued as a central benefit of data sharing, allowing others…
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Cambridge Data Week 2020 day 3: Is data management just a footnote to reproducibility?
Cambridge Data Week 2020 was an event run by the Office of Scholarly Communication at Cambridge University Libraries from 23–27 November 2020. In a series of talks, panel discussions and interactive Q&A sessions, researchers, funders, publishers and other stakeholders explored and debated different approaches to research data management. This blog is part of a series summarising each event: The rest of the blogs comprising this series are as follows:Cambridge Data Week day 1 blogCambridge Data Week day 2 blogCambridge Data Week day 4 blogCambridge Data Week day 5 blog Introduction The third day of Cambridge Data Week consisted of a panel discussion about the relationship between reproducibility and Research Data…
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Cambridge Data Week 2020 day 4: Supporting researchers on data management – do we need a fairy godmother?
Cambridge Data Week 2020 was an event run by the Office of Scholarly Communication at Cambridge University Libraries from 23–27 November 2020. In a series of talks, panel discussions and interactive Q&A sessions, researchers, funders, publishers and other stakeholders explored and debated different approaches to research data management. This blog is part of a series summarising each event: The rest of the blogs comprising this series are as follows:Cambridge Data Week day 1 blogCambridge Data Week day 2 blogCambridge Data Week day 3 blogCambridge Data Week day 5 blog Introduction How should researchers’ data management activities and skills be supported? What are the data management responsibilities of the funder, the institution, the research group…
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Cambridge Data Week 2020 day 5: How do we peer review data? New sustainable and effective models
Cambridge Data Week 2020 was an event run by the Office of Scholarly Communication at Cambridge University Libraries from 23–27 November 2020. In a series of talks, panel discussions and interactive Q&A sessions, researchers, funders, publishers and other stakeholders explored and debated different approaches to research data management. This blog is part of a series summarising each event: The rest of the blogs comprising this series are as follows:Cambridge Data Week day 1 blogCambridge Data Week day 2 blogCambridge Data Weekday 3 blogCambridge Data Week day 4 blog Introduction Cambridge Data Week 2020 concluded on 27 November with a discussion between Dr Lauren Cadwallader (PLOS), Professor Stephen Eglen (University of Cambridge) and Kiera McNeice (Cambridge University Press) on models of data peer…
