SHARING RESEARCH DATA POLICY, INFRASTRUCTURE, PEOPLE

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1 SHARING RESEARCH DATA POLICY, INFRASTRUCTURE, PEOPLE... VEERLE VAN DEN EYNDEN... MANAGER RESEARCH DATA MANAGEMENT SUPPORT SERVICES UNIVERSITY OF ESSEX, UK... CHPC NATIONAL MEETING DECEMBER 2010

2 OVERVIEW Effective sharing of research data requires policy support data sharing infrastructures researcher skills needs and incentives

3 curator of the largest collection of digital data in the social sciences and humanities in the United Kingdom easy access to data: search, browse and download enhance data for research and teaching user guides and documentation support for researchers, data creators and data users

4 SOURCES OF DATASETS government survey data individual academics - research grants (ESRC and BA funded) market research agencies public records and historical data international statistical time series qualitative, quantitative and crossdisciplinary data 5000 datasets in the collection 230 new datasets each year over 46,000 registered users approx.60,000 downloads worldwide per year user support queries access to international data via links with other data archives worldwide

5 DATA POLICY Economic and Social Research Council (ESRC) data policy (2000, 2010) publicly-funded research data = public good & should be openly available where possible define roles and responsibilities of researchers, research council & data service providers UK Data Archive Economic and Social Data Service Dialogue with ESRC re. policy development e.g. data management and sharing plans from 2011 Data policies mandating / encouraging data sharing Organisation for Economic Cooperation and Development most UK research councils various international research funders see

6 PUBLISHER POLICIES Publishers push data sharing data publishing policies may link with data centres / archives as places of deposit e.g. Nature publishing condition: data available preferably via public repositories; discipline-specific repositories are suggested; data standards, formats specifications e.g. PANGAEA = open access repository for various journals. Digital Object Identifiers (DOI) for data - unique and persistent identifier

7 DATA INFRASTRUCTURE preserving data data discovery data access structuring data At UK Data Archive: main collection self-archiving UKDA-store: Secure Data Service (SDS): linking with other data centres e.g. CEH Gateway (Centre for Ecology and Hydrology) https://gateway.ceh.ac.uk/

8 ESDS DATA CATALOGUE

9 SDS

10 UKDA-STORE

11 INFRASTRUCTURE UKDA metadata schema DDI (Data Documentation Initiative) controlled vocabularies e.g. HASSET keyword thesaurus Open Archives Initiative (OAI) metadata harvesting protocol E.g. Relu Knowledge Portal, linking archived data with publications in ESRC repository

12 RELU KNOWLEDGE PORTAL

13 TOOLS Dext Data Exchange Tools and Utilities data exchange tool for survey and quali data convert to open formats XML/RDF SQUAD - Smart Qualitative Data: Methods and Community Tools for Data Mark-Up XML tags in data standardised format web-enabled search/browse/display UKDA-store - self-archiving repository linking data and outputs Ensemble - Semantic Technologies for the Enhancement of Case Based Learning

14 RESEARCHER SKILLS Data management support for researchers advice and guidance training workshops data management plans Audiences: ESRC award holders, Relu researchers, Research Ethics Committees, data depositors, other data curators Identify researchers data management needs: researcher queries problems arising before or at data deposit stage active discussions with researchers data management plans

15 DATA MANAGEMENT CHALLENGES data confidentiality - how to share confidential data consent for data sharing anonymising data access regulation to data describing and documenting data for re-use data copyright researchers finding time to manage data well attitudes toward data sharing

16 DM RESOURCES online guidance - Managing and Sharing Data - a best practice guide for researchers data sharing vs data protection information for RECs report Data management practices in the social sciences help desk

17

18 DM TRAINING training workshops for researchers and support staff in social sciences and related disciplines why share research data and how ethics, consent and confidentiality when sharing data copyright and using existing data describing, documenting and contextualising data data formats and software data storage, back-up and security

19 DM PLANNING research funders increasingly expect researchers to develop data management and sharing plans and to manage data well throughout the research lifecycle review data management plans for Relu projects, and will for ESRC more generally work with research teams, research centres and programmes to help develop good data management planning strategies International engagement to share experiences e.g. IASSIST, MIT, ANDS, NSF

20 OUR DATA MANAGEMENT SERVICES UK Data Archive Research Data Management Support Services Economic and Social Data Services RELU-Data Support service relu.data-archive.ac.uk JISC Data Management Planning project ESRC Research Development Initiative Training Programme

21 EXAMPLE - RELU DATA SUPPORT SERVICE Rural Economy and Land Use Programme, cross disciplinary research programme social sciences, environmental and biological sciences Data Support Service, Relu-DSS data management plan at start of each research project need for access to existing data sources datasets planned to be produced planned quality assurance and back-up procedures for data plans for management and archiving of collected data expected difficulties in making data available for re-use measures to overcome such difficulties who holds copyright and intellectual property rights of data data management roles and responsibilities Relu-DSS reviews plans sign off, give advice data management guidance for award holders and grant applicants training workshops for researchers project visits to discuss data sharing and management at project level

22 RELU DMP EVALUATION expected difficulties to share data often underestimated, esp. for confidential, commercial or sensitive data if difficulties anticipated (ethical / legal), only few suggest solutions failure to gain consent for data sharing developed DMP is not necessarily implemented DMP makes researchers think about and discuss data issues within research team researchers want practical advice to be able to plan DM support service needs to give clear and specific advice that researchers understand

23 EXAMPLE DMP-ESRC PROJECT assessing current data management in ESRC centres and programmes: New Dynamics of Ageing (NDA) Centre for Research on Socio-Cultural Change (CRESC) Centre for Social and Economic Research on Innovation in Genomics (Innogen) Third Sector Research Centre (TSRC) help centres and programmes develop and implement effective data management planning in the research lifecycle increase individual and institutional data managing and sharing capacity

24 RECENT RECOMMENDATION FOR A CENTRE create data management resources library allocate data management contact for each project centre-wide data log standard ethical review forms (append additional items to standard institutional forms where necessary) use agreed consent forms and information sheets collate an anonymisation log using a proforma use transcription proformas and rules/confidentiality agreements for transcribers set up security policy for storing and sending data set up policy for retention and destruction of data create statement for copyright and ownership of data provide recommendations on using standard data formats set up file sharing and storage procedures set up version control and file naming guidelines

25 DATA SHARING NEEDS AND INCENTIVES ongoing dialogue in UK and beyond why share research data needs for access to data usually clear incentives for researchers to share data e.g. recognise as part of research excellence which data to preserve future uses difficult to estimate data sharing well establish in certain research fields e.g. climate change research, genetics research Reluctance in other domains data sharing infrastructure gaps e.g. medical data, agriculture, biotechnology

26 DATA REUSE CASE STUDIES

27 CONCLUDE policy infrastructure people All contribute to data sharing progress

28 QUESTIONS? RESEARCH DATA MANAGEMENT SUPPORT SERVICES UNIVERSIY OF ESSEX WIVENHOE PARK COLCHESTER ESSEX CO4 3SQ. T +44 (0) E

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