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Understanding the research environment & what support researchers need

Understanding the research environment & what support researchers need. Sarah Jones DCC, University of Glasgow sarah.jones@glasgow.ac.uk. a survey tool for scoping data management practices and needs.

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Understanding the research environment & what support researchers need

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  1. Understanding the research environment & what support researchers need Sarah Jones DCC, University of Glasgow sarah.jones@glasgow.ac.uk

  2. a survey tool for scoping data management practices and needs “enable all universities and colleges to carry out an audit of departmental data collections, awareness, policies and practice for data curation and preservation”

  3. Themes addressed in DAF surveys • Data: type / format, volume, description, creator, funder • Creation: policy, naming, versioning, metadata & documentation • Management: storage, backup, roles and responsibilities, planning • Access: restrictions, rights, security, frequency, ease of retrieval, publish • Sharing:collaborators, requirements to share, methods, concerns • Preservation: selection / retention, repository services, obsolescence • Gaps / needs: services, advice, support, infrastructure • www.data-audit.eu/docs/DAF_Implementation_Guide.pdf

  4. University of Oregon example • A survey using DAF and Purdue data curation profiles • Asked about data format, storage, access & KT, top issues / priorities • Data storage and backup far outweigh other concerns Brian Westra, Data Services for the Sciences: www.ariadne.ac.uk/issue64/westra/

  5. What support is needed? • Do researchers know what services are in place and use them? • Are services meeting researchers’ data management needs? • Is there coherence across the existing services? JISC MRD: http://www.jisc.ac.uk/whatwedo/programmes/mrd.aspx (see in particular the RDMI project strand)

  6. PLAN CREATE DATA ADD DOCUMENTATION RESEARCHERS IT DATA CENTRE Managing research data the activities and people involved in managing data What researchers need to consider at each stage? Is the support they need to do this in place?

  7. Planning data management Considerations • What do you (others) want to do with the data you are generating? • Can you choose appropriate standards / formats for this usage? • Who will have rights over any collaboratively generated data? • Do you have everything in place to manage data e.g. storage, skills etc Support • Ethics guidance – model agreements, advisory services • IPR guidance – is it clear who owns what and how to negotiate agreements? • Guidance on appropriate tools, software/formats – data plan support

  8. Creating / collecting data Considerations • What is the process for naming and versioning? • How will you control data quality across capture tools, people and sites? • Where will data be stored and backed-up - does everyone know who’s responsible for this? Support • Training courses on different software packages • Data support embedded within the project team - PhDs • Sufficient storage and back-up provision – is this in line with researchers’ needs

  9. Metadata and documentation Considerations • What information will future users will need to understand the data? • variable values, classification schema, project context, usage tipsle results • How will you make sure this is captured? • Are there standards you can use? Support • Advice on standards, examples of good approaches • role for subject librarians in terms of providing this support? • Knowledge of data centre standards to help researchers create quality data

  10. Access and data sharing Considerations • How are data transferred if you work remotely / share with colleagues? • emailed, copied on to portable storage, secondary copy • Are there more secure options? • Have you decided what data are appropriate to share and how this can be done? Support • What remote access provision is made and are people aware of it? • Identify and monitor potential risky cases e.g. flag sensitive data at proposal stage • Longer-term access and data sharing support through repositories

  11. Preservation Considerations • Are there requirements to keep data for the long-term? • How will you select what to keep? • Is there somewhere you can archive data, and do they have minimum standards? Support • University repository and archive? • how does this link in with external infrastructure? • External data centres e.g. • ICPSR (Social Science data)- http://www.icpsr.umich.edu/icpsrweb/ICPSR/ • NCAR (Atmospheric data) - http://ncar.ucar.edu/ • NSIDC (Snow & ice data) - http://nsidc.org/daac/ • NODC (Oceonograhic data) - http://www.nodc.noaa.gov/ • NSSDC (Space science data) - http://nssdc.gsfc.nasa.gov/ • PDB & UnitProt (Protein sequence data) - http://www.pdb.org/ and http://www.uniprot.org/

  12. Any questions?

  13. Exercise: how would you scope researchers’ support needs? • What would your key questions be? • How would you go about collecting information – survey methods, who will you ask? • How would you ensure participation?

  14. Coverage: Key questions to be asked? Examples from DAF projects are available in the Implementation Guide – http://www.data-audit.eu/docs/DAF_Implementation_Guide.pdf Other relevant data studies • Australian University survey, investigating data management - http://www.apsr.edu.au/orca/investigating_data_management.pdf • Data curation profiles: http://www4.lib.purdue.edu/dcp/ • Oxford University projects -www.ict.ox.ac.uk/odit/projects/digitalrepository/andhttp://eidcsr.blogspot.com/ • Purdue data interviews - http://docs.lib.purdue.edu/lib_research/81/ • RIN life science case studies - http://www.rin.ac.uk/our-work/using-and-accessing-information-resources/disciplinary-case-studies-life-sciences

  15. Collecting information • Desk based research, questionnaires, interviews, focus groups, co-locate/observation, diaries/information lab notebooks… • Speak to the full range of stakeholders including: • Researchers • Management / PIs • Computing services / local IT • Research support e.g. technicians, archivists, ethics advisors

  16. Audience engagement: Ensure participation? • Senior management approval • Internal advocate • Sell the benefits to the individual and institution • Imperial College – http://ie-repository.jisc.ac.uk/307/pp19-20 • University of Oregon business case for DAF audit - http://libweb.uoregon.edu/inc/data/faculty/datainventorybizcase.pdf

  17. Thanks Sarah Jones - sarah.jones@glasgow.ac.uk www.dcc.ac.uk/training www.data.audit.eu

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