1. Data Management Development and Implementation: an example from the UK SLA Conference, Boston, June 2015 Geraldine Clement-Stoneham Knowledge and Information Manager Medical Research Council UK

2. Encourage and support high-quality research with the aim of improving human health. Produce skilled researchers. Advance and disseminate knowledge and technology to improve the quality of life and economic competitiveness in the UK and worldwide. Promote dialogue with the public about medical research. MRC mission

3. MRC Strategic Plan 2014-2019 Research Changes Lives 2014-2019 Strategic intent: to support excellent discovery science and partnerships to promote translation to accelerate the pace of improvements in health and wealth. Strategic Aim One: Picking research that delivers Setting research priorities which are most likely to deliver improved health outcomes Strategic Aim Two: Research to people Bringing the benefits of excellent research to all sections of society Strategic Aim Three: Going global Accelerating progress in international health research Strategic Aim Four: Supporting scientists Sustaining a robust and flourishing environment for world-class research

4. My role at the MRC Policy advisor MRC Data Sharing Policy Survey external changes and impact on the MRC National and international policy harmonisation Research information - outputs Technical advisor Best practice and standards across data lifecycle Information management infrastructure Research information systems and data quality Records management

5. MRC Data Sharing Policy http://www.mrc.ac.uk/research/research-policy-ethics/data-sharing/policy/

6. European Commission - pilot action on open access to research data Must have a Data Management Plan and maintain it Deposit in a research data repository and take measures to make it possible for third parties to access, mine, exploit, reproduce and disseminate — free of charge for any user

7. Opportunities for re-use Photograph © CDC licenced under CC-BY Source: Flickr Data linkages and new discoveries – maximising the value of data collected through MRC funded research

8. Validation of results and research integrity Source: WSJ, Nature and Science

9. Source: ODI, Gov.uk, World Bank, International Business Times Economic and societal benefits

10. Data management lifecycle Thinking about data sharing from the incept of a research project Data Management Plan Good data management during the project Good information and records management practice Standard adoption How to archive the data at the end of the project Discoverability, sustainability, long term curation How to decide when data can be disposed of as it has reached the end of its valuable life Linking data

11. Example 1: Thinking upfront – developing data management plans Description of the data Data collection / generation Data management, documentation and Curation Data security and confidentiality of potentially disclosive information Data sharing and access Responsibilities Relevant institutional, departmental or study policies on data sharing and security Community effort to standardise vocabulary used in data management plans

12. Example 2: Assessing long term value of datasets Can we destroy this data set? Who sponsored the research? Who owns the IP? Cannot decide, but can still provide advice No What type of project is it? When did it end? What data is held? What is the data gathering period? Yes

13. Aspect to consider? What the current archiving arrangements (electronique, catalogued, etc) Is the re-usability likely? What was the impact of the research? Is it linked to a treatment still commonly in use? Have any claims be issued in relation to this research? What is the historical significance (e.g. 1 st treatment avilable for a particular disease, huge change in practice, novel way in which the research was conducted) What were the long term outcomes (for example if trial, are participants still alive) Are they any recent marketing authorisations? Is there a data management plan?

14. Decision process: clear and documented Internal and external information gathered and recommendation is written and presented Involve relevant stakeholders Primary Investigator Domain expert (usually programme manager) Be clear who has the relevant authority to sign off the decision Have advice as to where deposit data if current location in unsuitable Be clear that 10, 20 and 25 years are only appraisal stages, not automatic destruction

15. Example 3: Linking data

16. Research Information Management Illustration: Gavin Reddick, MRC

17. Useful information MRC Data Sharing policy MRC Data MRC policy on sharing of research data from population and patient studiesMRC Data MRC policy on sharing of research data from population and patient studies MRC Data Management Plan RCUK Principles on Data Sharing Policy European Commission Guidelines on data management in Horizon 2020European Commission Guidelines on data management in Horizon 2020 Data Curation Centre (DCC) UK Data Service Knowledge Exchange JISC Research Data Management Casrai

18. Thank you! geraldine.clement-stoneham@headoffice.mrc.ac.uk @geraldinecs Illustration © Damian Navas licenced under CC-BY-NC-NDCC-BY-NC-ND Source: Flickr