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Why Research Data Management is important: Workshop with graduate students of the School of Social and Political Science at the University of Edinburgh - 14 April 2015

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Short presentation for PhD and MSc students from the University of Edinburgh's School of Social and Political Science introducing the benefits of good practice in Research Data Management. Part of a morning workshop provided by the university's Data Library team.
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  • 1. P a u l i n e W a r d D a t a L i b r a r y A s s i s t a n t d a t a l i b @ e d . a c . u k Research Data Management 14 April 2015
  • 2. Research data management  Research data management (RDM) is caring for, facilitating access to, preserving and adding value to research data throughout its lifecycle.  Data management is part of good research practice.  Good research needs good data.  Take good care of your data, and it will take care of you!
  • 3. Activities involved in RDM  Data management Planning  Creating data  Documenting data  Storage and backup  Sharing data  Preserving data
  • 4. Activities involved in RDM Type, format volume of data, chosen software for long-term access, existing data, file naming, structure, versioning, quality assurance process. Information needed for the data to be read and interpreted in future, metadata standards, methodology, definition of variables, format & file type of data. Restrict access to data, risks to data security, appropriate methods to transfer / share data, encryption. Secure & sufficient storage for active data, regular backups, disaster recovery Make data publicly available (where possible) at the end of a project, license data, any restrictions on sharing, access controls? Select data to keep, decide how long data will be kept, in which repository, costs involved in long-term storage? Data Management Planning
  • 5. Why manage your data well?  So you can find and understand it when needed.  To avoid unnecessary duplication.  So you can finish your PhD!  To validate results if required.  So your research is visible and has impact.  To get credit when others cite your work.
  • 6. Why manage your data well?  “Data management… if you’re getting public funding to collect data, you have to leave data in a way that is usable for other people unless there [are] very good reasons not to do that. And you won’t leave it in ways that are usable for other people if you haven’t had good procedures for documenting it as you’ve gathered it. So even if you’re all right, because it fits your purpose, you’re diminishing its public value …” Professor Lynn Jamieson, Sociology, University of Edinburgh
  • 7. Why manage your data well?  “I think people often imagine secondary data analysis to be a highly planned, predictable activity. In practice it's rarely like that. It's fairly rare to plan to do something, to do it, and it works the way you wanted it to work first time. … It's important to log what you do as you do it each step of the way.” Professor John MacInnes, Sociology, University of Edinburgh
  • 8. Why manage your data well?  “..having a clear data management plan in research, … I think it is very helpful to know what you want from your data. So to sit down and think about:  What sort of data do I need?  Where will I get it from?  What might be the risks or problems of me getting that data? ..and to then be able to write down how you're going to make use of that data can be very helpful because you can refer back to it back later as you are going through things.” Ellie Bates, 3rd year PhD student (Geosciences, looking at patterns of vandalism)
  • 9. Drivers for data sharing
  • 10. ESRC Research data policy  “Data are the main assets of economic and social research. We recognise publicly-funded research data as valuable, long-term resources that, where practical, must be made available for secondary scientific research.”  “The data must be made available for re-use or archiving with the ESRC data service providers within three months of the end of the grant.”  “Whilst not compulsory, ESRC-funded students are strongly encouraged to offer copies of data created or repurposed during their PhD for deposit at the UK Data Service as it is considered good research practice.”
  • 11. ESRC Research data policy  “It is the grant holder’s responsibility to incorporate data management as an integral part of the research project.”  “We believe that a structured approach to data management results in better quality data that is ready to deposit for further sharing. Planning how you will manage your research data should begin early on in the research process ...”
  • 12. University of Edinburgh Research Data Management Policy  “All new research proposals [from date of adoption] must include research data management plans or protocols that explicitly address data capture, management, integrity, confidentiality, retention, sharing and publication.”  “The University will provide mechanisms and services for storage, backup, registration, deposit and retention of research data assets in support of current and future access, during and after completion of research projects.”  “Research data management plans must ensure that research data are available for access and re-use where appropriate and under appropriate safeguards.”
  • 13. Useful links  Digital Curation Centre (DCC): Data management plans http://www.dcc.ac.uk/resources/data-management-plans  Economic and Social Research Council: Research Data Policy (March 2015) http://www.esrc.ac.uk/about-esrc/information/data-policy.aspx  University of Edinburgh: Research Data Management Policy http://www.ed.ac.uk/schools-departments/information-services/about/policies-and- regulations/research-data-policy
  • 14. Acknowledgment Many thanks to Cuna Ekmekçioglu for providing the original slides on which this presentation is based.
  • 15. Any questions? Please give us feedback: datalib@ed.ac.uk
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