Research Data Management for Support Staff

1. Research Data Management for Support Staff Jonathan Rans & Kerry Miller, Digital Curation Centre

2. About this course • Short presentations with exercises and discussion • Five main sections • Research data and RDM (30 mins) • RDM at Surrey (15 mins) • Skills exercise • Data Management Planning (30 mins) • Data sharing (30 mins) • Breakout sessions – • Practical DMP support or Metadata and Documentation • Lunch @ 13:30

3. Introductions Introduce yourself and offer a reflection on the questions: • What is your understanding of research? • Do you know anything about data management? • What do you want to find out today? • How do you see yourself supporting RDM?

4. Research data and RDM

5. So, what is meantby ‘research data’? Anything & everything produced in the course of research

6. Defining research data • Research data are collected, observed or created, for the purposes of analysis to produce and validate original research results • Both analogue and digital materials are 'data' • Lab notebooks and software may be classed as 'data' • Digital data can be: • created in a digital form ('born digital') • converted to a digital form (digitised)

7. Types of research data • Instrument measurements • Experimental observations • Still images, video and audio • Text documents, spreadsheets, databases • Quantitative data (e.g. household survey data) • Survey results & interview transcripts • Simulation data, models & software • Slides, artefacts, specimens, samples • Sketches, diaries, lab notebooks …

8. What is data management? “the active management and appraisal of data over the lifecycle of scholarly and scientific interest” Digital Curation Centre

9. What is involved in research data management (RDM)? • Data Management Planning • Creating data • Documenting data • Accessing / using data • Storage and backup • Sharing data • Preserving data

10. What do research funders expect? http://www.dcc.ac.uk/resources/policy-and-legal/overview-funders-data-policies

11. RDM principles and advice to share with researchers n.b. Data Management Planning and Data Sharing are covered in separate sections See in particular: UK Data Archive, Managing and sharing data: best practice for researchers http://data-archive.ac.uk/media/2894/managingsharing.pdf

12. Data creation • Decide what data will be created and how - this should be communicated to the whole research team • Develop procedures for consistency and data quality • Choose appropriate software and formats - some are better for long-term preservation and reuse • Ensure consent forms, licences and partnership agreements don’t limit options to share data if desired

13. Documentation • Collect together all the information users would need to understand and reuse the data • Create metadata at the time - it’s hard to do later • Use standards where possible • Name, structure and version files clearly

14. Access and use • Restrict access to those who need to read/edit data • Consider the data security implications of where you store data and from which devices you access files • Choose appropriate methods to transfer / share data • filestores & encrypted media rather than email & Dropbox

15. Storage and backup • Use managed services where possible e.g. Surreyshared drives rather than local or external hard drives • Ask the local IT team for advice • 3… 2… 1… backup! • at least 3 copies of a file • on at least 2 different media • with at least 1 offsite

16. Data selection • It’s not possible – or desirable - to keep everything. • Select based on: • What has to be kept e.g. data underlying publications • What legally must be destroyed • What can’t be recreated e.g. environmental recordings • What is potentially useful to others • The scientific or historical value

17. Guidance on selection and appraisal http://www.dcc.ac.uk/resources/how-guides https://intranet.birmingham.ac.uk/as/libraryservices/records/guidelines.aspx http://www.nerc.ac.uk/research/sites/data/documents/data-value-checklist.pdf

18. Data preservation • Be aware of requirements to preserve data • Consult and work with experts in this field • Use available subject repositories, data centres and structured databases • http://databib.org • http://www.re3data.org/ • http://www.zenodo.org

19. Skills

20. How are support staff engaging in RDM? • Defining institutional strategy and policy • Implementing infrastructure • Advising researchers • Developing and delivering training • Supporting data management planning • Supporting data sharing • ... • www.dcc.ac.uk/community/institutional-engagements Research Office Library IT

21. When does RDM engagement happen? • Responding to researcher requests • Institutional support projects • Fulfilling funder requirements • FOI requests • Etc.

22. Exercise: skills to support RDM • Based on the activities we discussed earlier, consider who may have relevant skills or expertise to share. • You have 15 minutes

23. Conclusion

24. Acknowledgement • This Training has been adapted from the RDM for Librarians course created jointly by the DCC and the University of Northampton. Full details at: http://www.dcc.ac.uk/training/rdm-librarians

25. Acknowledgement Ideas and content have been taken from various courses: • Skills matrix, ADMIRe project, University of Nottingham http://admire.jiscinvolve.org/wp/2012/09/18/rdmnottingham-training-event • DIY Training Kit for Librarians, University of Edinburgh http://datalib.edina.ac.uk/mantra/libtraining.html • Managing your research data, Research360, University of Bath http://opus.bath.ac.uk/32296 • RDMRose Lite, University of Sheffield http://rdmrose.group.shef.ac.uk/?page_id=364 • RoaDMaP training materials, University of Leeds http://library.leeds.ac.uk/roadmap-project-outputs • SupportDM modules, University of East London http://www.uel.ac.uk/trad/outputs/resources