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Supporting Libraries in Leading the Way in Research Data Management

Marieke Guy, Institutional Support Officer, Digital Curation Centre, UKOLN, University of Bath, UK presents on Supporting Libraries in Leading the Way in Research Data Management at Online Information, London 20th -21st November 2012

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Supporting Libraries in Leading the Way in Research Data Management

  1. 1. Supporting Libraries inLeading the Way inResearch Data ManagementMarieke Guy, Institutional Support Officer,Digital Curation Centre, UKOLN, University of Bath, UKEmail: m.guy@ukoln.ac.ukTwitter Id: mariekeguyWeb: http://www.dcc.ac.ukOnline Information, 20th -21st November 2012 UKOLN is supported by: This work is licensed under a Creative Commons Licence Attribution-ShareAlike 2.0 1
  2. 2. Who Am I? • Have worked for UKOLN for over 12 years • Worked on variety of projects: Subject portals project, IMPACT, Good APIs, JISC Observatory, cultural heritage work, digital preservation work, …etc • Remote worker, into amplified events • Co-chair of IWMW for a number of years • Now working for Digital Curation Curation • Institutional Support Officer helping HEIs with their RDM2
  3. 3. Today’s Talk • Research data and why is it so important? • How research data is managed • What the DCC does • The role libraries are currently playing • The role libraries could be playing in the future3
  4. 4. http://www.google.co.uk/imgres?q=illumina+bgi&hl=en&client=firefox- a&hs=Jl2&rls=org.mozilla:en-GB:official&biw=1366&bih Research Datahttp://www.flickr.com/photos/thinkmulejunk/352387473/ http://www.flickr.com/photos/usf sregion5/4546851916 http://www.flickr.com/photos/wasp http://www.flickr.com/photos/charleswelch/3 _barcode/4793484478/ 4 597432481/
  5. 5. What is Research Data? …whatever is produced in research or evidences its outputs • Facts • Statistics • qualitative • quantitative • Not published research output “highest priority research data is that which • Discipline specific5 underpins a research output”
  6. 6. A Data Present “Data underpins our economy and our society - data about how much is being spent and where, data about how schools, hospitals and police are performing, data about where things are and data about the weather.” Tim Berners Lee, director of W3C.6
  7. 7. Big Data • Volume • Velocity • Variety “The 1000 Genomes Project generated more DNA “The 1000 Genomes Project generated more DNA sequence data in its first 6 months than GenBank sequence data in its first 6 months than GenBank7 had accumulated in its entire 21 year existence” had accumulated in its entire 21 year existence”
  8. 8. A Data Future “The ability to take data - to be able to understand it, to process it, to extract value from it, to visualise it, to communicate it -that’s going to be a hugely important skill in the next decades.” Hal Varian, Google’s chief economist.8 Hal Varian, Chief Economist, Google
  9. 9. Big Data…and Small Data • DIY data • Consumer data • Crowd Sourced data • What about Linked data/ Web of data/Open data? • Databases • Learning data • Administrative data • Long tail data r os s project: “ JIS C MaRDI-G ast significant e le ce vo lume is th resent context, sin ep (is sue) in th al problem ” hnic it i s ‘ o nly’ a tec9
  10. 10. Some Data Issues • Scale and complexity – data deluge – volume, pace • Infrastructure and management – Storage, costs & sustainability • Quality of data • Reputation – FOI, DPA, computer misuse • Openness agenda • Preservation • Working in partnerships • Funding for researchers10
  11. 11. Funding…the Biggest Carrot/Stick? EPSRC expects all those institutions it funds:•to develop a roadmap that aligns their policies and processes withEPSRC’s expectations by 1st May 2012;•to be fully compliant with these expectations by 1st May 2015.•http://www.epsrc.ac.uk/about/standards/researchdata/Pages/expectations.aspx11
  12. 12. Data Policies of Funders http://www.dcc.ac.uk/resources/policy-and-legal/overview-funders-data-policies12
  13. 13. What is Research Data Management? “the active management and appraisal of data over the lifecycle of scholarly and scientific interest” Data management is part of good research practice13
  14. 14. How is Research Data Managed? Some areas to think about: Leicester University Data management support for researchers Web site • Storage & cloud • Curation • Data repositories • Digital Preservation • Metadata & citation • Migration • File naming • Sharing/openness • Appraisal, selection & • Security deletion • Cost14
  15. 15. RDM Activities What kind of activities are involved? – producing and sharing of data with research colleagues in collaborative environments (internal and external) – file naming – applying metadata for context and discovery – ensuring that sensitive data is not shared or accessible – cleaning data for longer-term use – selecting mechanisms for data capture and storage – selecting and appraising data for short and longer-term retention – licensing data for reuse – developing data management plans •Data management is about making informed decisions15
  16. 16. The Digital Curation Centre • A consortium comprising units from the Universities of Bath (UKOLN), Edinburgh (DCC Centre) and Glasgow (HATII) • launched 1st March 2004 as a national centre for solving challenges in digital curation that could not be tackled by any single institution or discipline • Funded by JISC with additional HEFCE funding from 2011 for the provision of support to national cloud services • Targeted institutional development • http://www.dcc.ac.uk/16
  17. 17. Advocacy and Training How to… • Appraise and Select Research Data • Cite Datasets and Link to Publications • Develop a Data Management and Sharing Plan • License Research Data • Set a RDM service – coming soon!How to cite data17
  18. 18. 18
  19. 19. DCC Tools for Engagement Survey and interview methodology for investigating data holdings and how they are managed Capability model for establishing consensus on capabilities and gaps in current provision, rating organisation, technology and resources Customised institutional templates for data management planning19
  20. 20. Institutional Engagement Work • Funded by the HEFCE through its Universities Modernisation Fund (UMF) • Intensive, tailored support to increase research data management capability • Originally 18 Higher Education Institutions (HEIs) between Summer 2011 and Spring 2013 • Can help: – win the support of senior management – understand current data practices – redesign data support services – Help with policy development and training20
  21. 21. What Part are Libraries Playing? • RDM requires the input of all support services, but libraries are taking the lead in the UK • The library is leading on most of the DCC engagements Other examples include: –EDINA at University of Library Information Edinburgh managementthe a –Bodleian Library at is University of Oxford Research key skill in RDM, so –Subject librarians at Office it’s a major role for University of Southampton IT librarians21
  22. 22. Why are Libraries Taking the Lead? Because libraries: •Often run publication repositories so are the stakeholder called on when questions are raised about the management of associated data •Have directed the open sharing of publications so are well placed to advice on how best to support data requirements •Have good relationships with researchers and good connections with other service departments •Have a highly relevant skill set22
  23. 23. An Exciting Opportunity “Researchers need help to manage their data. This is a really exciting opportunity for libraries….” Liz Lyon, VALA 2012 • Leadership • Providing tools and support • Advocacy and training • Developing data informatics capacity & capability23
  24. 24. Reskilling for Research But librarians feel they lack appropriate skills… Skills gap 2-5 years Now Preserving research outputs 49% 10% Data management & curation 48% 16% Complying with funder mandates 40% 16% Data manipulation tools 34% 7% Data mining 33% 3% Metadata 29% 10% Preservation of project records 24% 3% Sources of research funding 21% 8% Metadata schema, disciplinary standards, practices 16% 2% From RLUK, Re-skilling for Research, Jan 2012, p4324 Other surveys include DataOne, Cologne Uni, DigCurV
  25. 25. Specialist Knowledge “Very few librarians are likely to have specialist scientific or medical knowledge - if you train as a research scientist or a medic, you probably won’t become a librarian.” Mary Auckland: Reskilling for Research 2012, RLUK.25
  26. 26. Knowledge Needed… • Librarians are overtaxed already, lack personal research experience, have little understanding of complexity and scale of issue • Need knowledge and understanding of: – Researchers’ practice and data holdings – Research Councils and funding bodies’ requirements – Disciplinary and/or institutional codes of practice and policies – Existing institutional policies and infrastructure – Reputational risks associated with poor data management – with respect to researchers’ reputations as well as that of their institutions – Data management and sharing benefits – Research data management tools and technologies26
  27. 27. And Needed Fast… Implications of “Big Data” and data science for organisations in all sectors McKinsey Global Institute predicts a shortage of 190,000 data scientists by 2019http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Inno 27vation/Big_data_The_next_frontier_for_innovation
  28. 28. Is Retooling Possible? “Significant mismatches exist between research data and library digital warehouses, as well as the processes and procedures librarians typically use to fill those warehouses. Repurposing warehouses and staff for research data is therefore neither straightforward nor simple; in some cases, it may even prove impossible.” Salo, D. (2010) Retooling Libraries for the Data Challenge, Ariadne, Issue 64. • Libraries are organised, research data isn’t • Need technical systems such as sheer curation, better sharing of data and improved funding models28
  29. 29. Possible Approaches • University of Helsinki Library – Knotworking “collaborative performance between otherwise loosely connected actors and activity systems” • University Burnaby, British Columbia - providing research data services since the 1970s – currently exploring funding gaps • Deutsche Nationalbibliothek - DP4lib project (Digital Preservation for libraries) where the library is acting as a service-broker for digital data curation • Research libraries - Opportunities for Data Exchange (ODE) project as an exemplar project, which gives shares emerging best practice • Data intelligence 4 librarians, Delft University of Technology29
  30. 30. Training Librarians: RDMRose • JISC funded project to produce OER learning materials in RDM tailored for Information professionals • Led by Sheffield University iSchool • Practitioner community based on the White Rose University Consortium’s libraries at the Universities of Leeds, Sheffield and York • Deliverables include curriculum, module within taught masters course in Sheffield, self study version • Much of course concentrates on teaching librarians about research and the research process • RDMRose working with Stephen Pinfield on a web-based survey of current library RDM activity • http://www.sheffield.ac.uk/is/research/projects30
  31. 31. Informatics Transform • Library & institutional stakeholders • Roles (7 listed): Responsibilities, Requirements, Relationships 1. Director IS/CIO/University Librarian 2. Data librarians /data scientist / liaison/subject/faculty librarians 3. Repository managers 4. IT/Computing Services 5. Research Support/Innovation Office 6. Doctoral Training Centres 7. PVC Research Liz Lyon, Informatics Transform, Ariadne Issue 68, 201231
  32. 32. Partnership Approaches • Research 360, University of Bath: • UKOLN-DCC • Library • IT services • Research Support Office • Doctoral Training Centres http://blogs.bath.ac.uk/research360/32
  33. 33. Embedded Librarians “Librarians may need to raise their profile, become ‘researchers’ themselves; getting embedded in the research community; gaining credibility; and collaborating as equals.” Bent et al, Information literacy in a researchers learning life in New Review of Information Networking, 13 (2), 200733
  34. 34. So What Next? • Address the lack of data informatics skills • Mainstream data librarians & data scientists • Embed new skills into LIS & iSchool curriculum Lyon, ‘The Informatics Transform: re-engineering libraries for the data decade’ in IJDC, 7(1), 2012 hts the an ag ement highlig bracing Re search data m n’s skillset. By em licability of the libraria t, librarians will ap p u ppo r p rovide RDM s d as . the need to of institutional agen remain at the heart34
  35. 35. Resources to Look at… • Riding the Wave report and many others emphasise the relevance of research data to current academic working • RLUK/Mary Auckland: Reskilling for Research • Sheila Corrall: Libraries, Librarians and Data • DigCurv • Book: Managing Research Data • HEIs research data support pages35
  36. 36. Thank You • Thanks to DCC colleagues for contributing to slide material. Any questions? m.guy@ukoln.ac.uk36