Digital curation for postgraduate students

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    14-Jan-2015

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DESCRIPTION

Slides from a DC101 workshop run at the University of Northumbria on behalf of the JISC-funded DATUM for Health project.

Transcript

1. Digital Curation for PGR StudentsJoy Davidson and Sarah JonesHATII and the Digital Curation Centrejoy.davidson@glasgow.ac.uksarah.jones@glasgow.ac.ukDATUM for Health 2. Session aims and objectivesAimed at PGRs, well use the context of starting a PhD to:introduce the curation lifecycle model as a means of contextualizing the roles and activities required to maintain access to data over timehighlight some of the curation tools and approaches available and provide pointers to further information and support help participants prepare the curation aspects of their PhD studyWe hope you leave able to explain why data curation is important andwhat roles PGR students / researchers play 3. What is data curation?the active management and appraisal of data over the lifecycle of scholarly and scientific interestData have importance as the evidential base of scholarly conclusionsCuration is part of good research practice 4. Why curate: requirementsCode of good research conductdata should be preserved and accessible for 10 years +declarationdata are a public good and should be openly availableFunders data policieswww.dcc.ac.uk/resources/policy-and-legal/funders-data-policiesCommon principles on data policywww.rcuk.ac.uk/research/Pages/ DataPolicy.aspx 5. Why curate: rewardsPrevent data lossMore citations: 69% (Piwowar, 2007 in PLoS)Validation of resultsNew research opportunities and collaborationsEasier to do your research 6. DCC curation lifecycle model 7. Conceptualise: planning what to doActivities define a research question and design your methodology 8. bid for funding (incl. data management and sharing plans) 9. plan data creation (capture methods, standards, formats)RolesPGR student, supervisory team, sponsors / funding bodies, IT, research governance, ethics panel Decisions made now have an impact on every other stage of the lifecycle, so it is worth getting things right from the start! 10. Specific issues to consider Defining your method access to software, equipment, skills 11. What storage needs do you anticipate - enough capacity? 12. What are your universitys / sponsors requirements? 13. What ethical approval do you require? 14. What agreements do you have to establish at the outset? 15. Will you make use of any existing data licences needed? 16. Can the data be shared? 17. Are there any legal or ethical restrictions? 18. Are there likely to be any embargoes on data publication?

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