Good practice in Research Data Management Module 2: RDM Introduction

Topics What is Research Data Management (RDM)? Why is RDM is important – National landscape and external drivers – Newcastle University response/policy/implications Benefits & barriers

WHAT IS RDM?

What is RDM? “Research data management concerns the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results.” Whyte & Tedds,

RDM is about… Caring for… Facilitating access to… Preserving… Adding value to… digital research data throughout its lifecycle

Activities involved in RDM CreateDocumentUseStoreSharePreserve

ACTIVITY: YOUR RESEARCH DATA CYCLE

Your data cycle: feedback Can you improve your research data management? Where are the weak points? Are you at risk of losing data?

WHY IS RDM IMPORTANT?

Holistic perspective Good data management is good for research – More efficient research process – Avoidance of data loss – Benefits of data reuse

HE perspective Alignment with universities' missions – Universities want to provide excellent research infrastructure – Universities want to have better oversight of research outputs

External drivers Research funder policies – Require Open Access, RDM plans or 'technical appendices' Legislation & litigious environment – DPA, FOIA Open data agenda Volume of digital research data

Newcastle University perspective Significant academic and financial implications for Newcastle University In direct research income was £88 million REF associated Quality-Related funding returns £35 million annually

Newcastle University perspective #2 Public funders now mandate that research data produced through their funding are available openly for verification, validation and re-use RCUK roadmap of compliance – EPSRC strictest May 2012 – May

Newcastle University perspective #3 Newcastle University is committed to the full lifecycle of research management Investment in systems Major Jisc-funded project: Iridium Documentation and support –

Newcastle University draft RDM policy Newcastle University draft RDM policy and Code of Good Practice available online (pdf) – gementPolicyPrinciplesandCodeofGoodPractice.pdf gementPolicyPrinciplesandCodeofGoodPractice.pdf Consider alongside other policies which may affect you and your data – dance/Policies.htm dance/Policies.htm

10 policy principles (1-3) 1.Research data management (including costs) should be considered at the earliest practical stage of the project and reviewed regularly to ensure that practice remains in- line with expected standards. 2.The project Principal Investigator (PI) at Newcastle University has overall responsibility for the appropriate storage, treatment (including making data sets suitable for publication) and security of research project data. 3.PI’s can delegate discrete responsibilities and this should be outlined in the research data management plan or appropriate project documentation.

10 policy principles (4-7) 4.All University staff are responsible for making themselves familiar with and adhering to legislation, funder guidance and University policy governing their research data. 5.The PI must provide the University with access instructions to research data within 4 weeks of successful publication. 6.Published datasets should be as comprehensive as possible and have clear instructions for access. Metadata should be rich enough to facilitate discovery, reproduction and reuse. 7.Research data should remain available for 10 years following any publication (unless otherwise specified) after which retention will be reviewed. Metadata will be kept indefinitely.

10 policy principles (8-10) 8.Researchers should deposit their data in an appropriate funder mandated or discipline specific data repository. Where this is not available data should be deposited in an approved centre / manner. 9.The University undertakes to provide appropriate resources, training, support and guidance to researchers and research support staff around data management. It will also provide a mechanism to record research metadata and to manage access. 10.Where data has a commercial value or supports a commercial output such as a patent then public disclosure of the data may be delayed (this should be agreed in consultation with Research & Enterprise Services).

ACTIVITY: NCL RDM POLICY PRINCIPLES AND YOU

Instructions Annotate the draft Ncl RDM principles, considering your research/research project – Where does responsibility lie? – Grade how comfortable you are with each item  

BENEFITS AND BARRIERS

Benefits and barriers of good RDM What are the benefits? – For the researcher? – For the "public good"? – For compliance? What are the barriers?

Benefits for the researcher Increased efficiency, time saving Improved use of resource(s), reduced duplication Enhanced data security and reduced risk of data loss Stimulation of new collaborations and new research opportunities

Benefits for the "public good" Data and records are accurate, complete, authentic and reliable Research integrity and replication Better spending of the "public purse" Better research and knowledge

Benefits of compliance Meet funding body grant requirements Comply with practices conducted in industry and commerce Comply with legal and ethical considerations Comply with publisher requirements

Barriers to good RDM Individual barriers – "My data doesn't fit RDM" – "It's my data!" – "I just want to get on with the research!" – "I don't understand RDM or what to do about it" Institutional barriers – Authority structures in universities – Insufficient local infrastructure to support RDM requirements – No checking of compliance internally Academic culture barriers – Informal sharing practices already exists – Lack of reuse culture – Legal, ethical and commercial motives

SESSION REVIEW

In summary RDM concerns the careful management of data throughout its lifecycle Newcastle University is making a strong institution-wide response The benefits outweigh the barriers!

Acknowledgements Digital Curation Centre (DCC) – RDM Rose, Jisc project , University of Sheffield – ose ose Research data MANTRA [online course], EDINA and Data Library, University of Edinburgh –