1. Preserving your research data for future use This work is licensed under a Creative Commons Attribution 3.0 Unported License.Creative Commons Attribution 3.0 Unported License

2. Overview Why manage research data? Lifecycle of research data What is research data? What is research data management How to store data Outline your own plan and steps to implementing it Information sources Summary

3. By the end of the session you will be better able to: Describe the forms research data takes and the role of contextual documentation and metadata in enabling data reuse Describe how managing research data effectively will improve your research, save you time, decrease the risks of data loss and increase your professional impact and identify tools to help Describe University of Leeds and research funder data management expectations Identify sources of information and guidance on managing research data effectively, including additional training courses

4. Why manage research data?

5. Why What represents your research For you? For others? Value of the data For you? For others? How is research validated?

6. Reusing data Do you still understand your older work? Is the file structure / naming understandable to others? Which data has been kept? Which data was discarded? How much was planned, how much was circumstance? UoB

7. Reasons to manage your data Responsible conduct of research Funding body grant requirements Research integrity and replication Increase research efficiency Save time and resources Enhance data security Prevent duplication of effort by enabling others to use your data UoD

8. Example

9. The lifecycle of research data

10. A lifecycle for research data Collect data Record data Process data Publish research

11. Make the underlying data available Collect data Record data Process data Publish research Publish data

12. Extent of recording data Collect data Record data Active use Archive Preserve Curate Process data Publish research Publish data

13. A hierarchy of keeping Archive to place or store in an archive; in Computing, to transfer to a store containing infrequently used files, or to a lower level in the hierarchy of memories, esp. from disc to tape. [OED Online] identifying and storing research objects for short,medium and long term use Preserve to keep in its original or existing state; to make lasting [OED Online] ensure data can be read in the future Curate to look after and preserve [OED Online] continued preservation ensuring what was put in is what comes out

14. Research protocols Collect data Record data Active use Archive Preserve Curate Process data Publish research Publish data Research method

15. Research protocols Collect data Record data Active use Archive Preserve Curate Process data Publish research Publish data Research method protocols form of meta data research data management plan

16. Access control Collect data Record data Process data Publish research Publish data Access control Data protection IPR

17. What is research data?

18. What are Data? The lowest level of abstraction from which information and knowledge are derived Research data are collected, observed or created, for the purposes of analysis to produce and validate original research results Both analogue and digital materials are data Digital data can be: created in a digital form ("born digital") converted to a digital form (digitised) UoB

19. Data types Data TypesValueExample Observational data captured around the time of the event Usually irreplaceableSensor readings, telemetry, neuro- images, survey results Experimental data from lab equipment Often reproducible but can be expensive Gene sequence, chromatograms, toroid magnetic field readings Simulation data generated from test models Model and metadata more important than output data Large modules can take a lot of computer time to reproduce Climate models, economic (inputs) models. Derived or compiled dataReproducible (but very expensive) Text and data mining, compiled databases, 3D models UoB

20. What research data do you have? Images from http://office.microsoft.com/en-gb/images

21. What do you do with your research data? What sort of research data do you have? How do you record/save/keep your research data? How do you process/analyse your research data? Collect data Record data Process data

22. What is this data? ix+viii=xi

23. What is this date? 110612

24. Metadata Contextual information for data is called metadata literally data about data Data repositories & archives require some generic metadata, e.g. author, title, publication date For data to be useful, it will also need subject-specific metadata e.g. reagent names, experimental conditions, population demographic Record contextual information in a text file (such as a ‘read me’ file) in the same directory as the data e.g. codes for categorical survey responses ‘999 indicates a dummy value in the data’ More info: http://www.data-archive.ac.uk/create-manage/documenthttp://www.data-archive.ac.uk/create-manage/document UoB

25. What do you do with your research data? What sort of research data do you have? How do you record/save/keep your research data? How do you process/analyse your research data? What meta data do you have? Collect data Record data Process data

26. Data Management Planning

27. … because good research needs good data What is Research Data Management (RDM)? An umbrella term to describe all aspects of planning, organising, documenting, storing and sharing data. It also takes into account issues such as data protection and confidentiality. It provides a framework that supports researchers and their data throughout the course of their research and beyond.

28. … because good research needs good data The DMP Checklist The DMP Checklist (Donnelly/Jones) is the underlying intellectual framework which supports all of the DCC’s data management planning work. The next part of this talk gives a very quick overview of these sections.

29. … because good research needs good data The DMP Checklist Pulled together a list of all the UK funders’requirements, gathered them into thematic groups, and supplemented this list with their own expertise... (Donnelly & Jones, 2009) This became the first ‘Data Management Plan Content Checklist’ (Checklist v1.0’) – it had 51 questions/headings. Post-consultation, v2.0 had 115 questions/headings. Version 3 was produced in March 2011 and has 118 questions A new, shorter version of the checklist is currently being worked on

30. … because good research needs good data DMP Checklist Headings The checklist covers all of the following areas: 1.Introduction and Context 2.Data Types, Formats, Standards and Capture Methods 3.Ethics and Intellectual Property 4.Access, Data Sharing and Re-use 5.Short-Term Storage and Data Management 6.Deposit and Long-Term Preservation 7.Resourcing 8.Adherence and Review 9.Agreement/Ratification by Stakeholders 10.Annexes Checklist for a Data Management Plan (Donnelly and Jones, last revision March 2011)

31. … because good research needs good data 1: Introduction and Context Basic project and administrative information Aims and purpose of the research Relevant policies (institutional, departmental, funder- specific...) Data (and metadata) specifics New and existing data Justifications of decisions 2: Data Types, Formats, Standards and Capture Methods

32. … because good research needs good data 3: Ethics and Intellectual Property Ethical and privacy issues (inc. Data Protection Act) Ownership of datasets Licensing of datasets Plans for sharing data / making accessible Freedom of Information Re-use expectations Embargoes, publications etc. 4: Access, Data Sharing and Re-use

33. … because good research needs good data 5: Short-Term Storage and Data Management In-project data management specifics Storage media Backups Security Long-term strategy (post-project) Selection Retention Transformation Longer-term custody 6: Deposit and Long-Term Preservation

34. … because good research needs good data 7: Resourcing Roles and responsibilities for implementation Funding (in-project and post-project) Roles and responsibilities Timetable for review / versioning 8: Adherence and Review §9: Agreement/Ratification by Stakeholders Statement of agreement (if needed) Contact details and expertise of named individuals Glossary of terms Other annexes as required §10: Annexes

35. … because good research needs good data Group exercise (20 minutes) In groups of 4 or 5: Read the materials that have been handed round; Thinking as a reviewer compare the 2 plans against the ESDS guidance you have been given; Identify the strengths and weaknesses of each; Which one of these plans would you approve? What changes would you want made to the other plan before it would gain approval?

36. Approaches to Preserving and Managing Research Data

37. Levels of managing data Use meta data tools Structure files Document the research

38. Consider Data format File formats Organising files Structure File names Data storage Volume Format (optical, magnetic) Security Backup

39. What is your experience of finding files? Challenges? Solutions?

40. Planning your data management

41. Your plan In groups Use the proforma provided Start to develop a plan for how to manage your research data

42. Summary

43. Managing research data is part of good research practice The data allows you to justify your research findings Enables you to more easily find and reuse your research data Managed data can be shared with others A research data management plan helps in achieving this Be clear about who is responsible for research data and its management

44. References Digital Curation Centre MIT Libraries on Data Management and Publishing Research Councils UK on Governance of Good Research UK Data Archive University of Leeds on Safeguarding data Research Data Management Data Protection Your funders requirements