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Planning for Research Data Management

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Slides from a workshop delivered on 20th February 2018 for OU researchers

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Planning for Research Data Management

  1. 1. Dan Crane Research Support Librarian library-research-support@open.ac.uk Planning for Research Data Management 20th February 2018
  2. 2. • What is Research Data Management? • Planning for RDM • Useful resources • Questions? Overview of the workshop
  3. 3. What do you hope to get from today? Overview of the workshop
  4. 4. What is Research Data Management? “Research data management concerns the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results. It aims to ensure reliable verification of results, and permits new and innovative research built on existing information." Digital Curation Centre (2011) Making the Case for Research Data Management http://www.dcc.ac.uk/sites/default/files/documents/publications/Making%20the%20case.pdf
  5. 5. What is Research Data Management? UK Data Archive Data Lifecycle model http://www.data-archive.ac.uk/create-manage/life-cycle Design research Plan data management Plan consent for sharing Locate existing data Collect data Capture and create metadata Creating data
  6. 6. http://www.data-archive.ac.uk/create-manage/life-cycle Enter data, digitise, transcribe, translate Check, validate, clean data Anonymise data Describe data Manage and store data Processing data What is Research Data Management? UK Data Archive Data Lifecycle model
  7. 7. http://www.data-archive.ac.uk/create-manage/life-cycle Interpret data Produce research outputs Author publications Prepare data for publications Analysing data What is Research Data Management? UK Data Archive Data Lifecycle model
  8. 8. http://www.data-archive.ac.uk/create-manage/life-cycle Migrate data to best format Migrate data to suitable medium Back-up and store data Create metadata and documentation Archive data Preserving data What is Research Data Management? UK Data Archive Data Lifecycle model
  9. 9. http://www.data-archive.ac.uk/create-manage/life-cycle Distribute data Share data Control access Establish copyright Assign licences Promote data Giving access to data What is Research Data Management? UK Data Archive Data Lifecycle model
  10. 10. http://www.data-archive.ac.uk/create-manage/life-cycle Follow-up research New research Undertake research reviews Scrutinise findings Teach and learn Re-using data What is Research Data Management? UK Data Archive Data Lifecycle model
  11. 11. • So you can work efficiently and effectively –Save time and reduce frustration –Highlight patterns, connections or errors that might otherwise be missed • Because your data is precious • To enable data re-use and sharing • To meet funders’ and institutional requirements What is Research Data Management? Why spend time and effort on this?
  12. 12. “Research data must be managed to the highest standards throughout their lifecycle in order to support excellence in research practice.” “In keeping with OU principles of openness, it is expected that research data will be open and accessible to other researchers, as soon as appropriate and verifiable, subject to the application of appropriate safeguards relating to the sensitivity of the data and legal and commercial requirements.” OU Research Data Management Policy, November 2016 http://www.open.ac.uk/library-research-support/sites/www.open.ac.uk.library- research-support/files/files/Open-University-Research-Data-Management-Policy.pdf What is Research Data Management? What does the OU expect?
  13. 13. “Good data management is fundamental to all stages of the research process and should be established at the outset.” “Open access to research data is an enabler of high quality research, a facilitator of innovation and safeguards good research practice.” Concordat on Open Research Data http://www.rcuk.ac.uk/documents/documents/concordatonopenresearchdata-pdf/ What is Research Data Management? What do funders expect?
  14. 14. http://www.dcc.ac.uk/resources/policy-and-legal/overview-funders-data-policies What is Research Data Management? What do funders expect?
  15. 15. • Support from the library research support team and website http://www.open.ac.uk/library- research-support/ What is Research Data Management? What does the OU provide?
  16. 16. • A repository, (ORDO) which meets funder requirements, facilitating secure, long-term storage of data https://ou.figshare.com/ What is Research Data Management? What does the OU provide?
  17. 17. “Start as you mean to go on” Thinking about the requirements at the beginning of the project will limit the work needed during and at the end of the project. Finish Planning for RDM
  18. 18. A project document which describes: • the data that a project will collect • how they will be stored during the project • how they will be archived at the end of the project • how access will be granted to them where appropriate. The Data Management Plan Planning for RDM
  19. 19. • Make informed decisions to anticipate and avoid problems • Avoid duplication, data loss and security breaches • Develop procedures early on for consistency • Ensure data are accurate, complete, reliable and secure • Save time and effort – make your life easier! Data Management Plans are useful whenever you are creating data to: Planning for RDM
  20. 20. Data Collection What data will you collect or create? How will the data be collected or created? Data Management Plan example Planning for RDM
  21. 21. Data Collection What data will you collect or create? How will the data be collected or created? Data Management Plan example Documentation and Metadata What documentation and metadata will accompany the data? Planning for RDM
  22. 22. Data Collection What data will you collect or create? How will the data be collected or created? Data Management Plan example Documentation and Metadata What documentation and metadata will accompany the data? Ethics and Legal Compliance How will you manage any ethical issues? How will you manage copyright and Intellectual Property Rights (IPR) issues? Planning for RDM
  23. 23. Storage and Backup How will the data be stored and backed up during the research? How will you manage access and security? Data Management Plan example Planning for RDM
  24. 24. Storage and Backup How will the data be stored and backed up during the research? How will you manage access and security? Data Management Plan example Selection and Preservation Which data should be retained, shared, and/or preserved? What is the long-term preservation plan for the dataset? Planning for RDM
  25. 25. Storage and Backup How will the data be stored and backed up during the research? How will you manage access and security? Data Management Plan example Selection and Preservation Which data should be retained, shared, and/or preserved? What is the long-term preservation plan for the dataset? Data Sharing How will you share the data? Are any restrictions on data sharing required? Planning for RDM
  26. 26. Storage and Backup How will the data be stored and backed up during the research? How will you manage access and security? Data Management Plan example Selection and Preservation Which data should be retained, shared, and/or preserved? What is the long-term preservation plan for the dataset? Data Sharing How will you share the data? Are any restrictions on data sharing required? Responsibilities and Resources Who will be responsible for data management? What resources will you require to deliver your plan? Planning for RDM
  27. 27. • Describe your research • What type of data do you create/use? • What data management challenges do you face? Planning for RDM Discussion For 5 minutes
  28. 28. Filing is more than saving files, it’s making sure you can find them later in your project • Naming • Directory Structure • File Types • Versioning All these help to keep your data safe and accessible. Data collection
  29. 29. Decide on a file naming convention at the start of your project. Useful file names are: • consistent. • meaningful to you and your colleagues. • allow you to find the file easily. Agree on the following elements of a file name: • Vocabulary • Punctuation • Dates (YYYY-MM-DD) • Order • Numbers • Version information Ideally you should be able to tell what’s in a file before opening it. Tip: create a readme file detailing the naming scheme. Data collection Naming conventions
  30. 30. Data collection Naming conventions – what to avoid… Dan.doc My paper.doc Results.xls August Mtg.doc 20June.csv IMPORTANT.pdf Article_Manuscript October_FINAL.doc Article_Manuscript October_FINAL FINAL.doc Article_Manuscript October_FINAL FINALv1.doc Article_Manuscript October_FINAL FINALv2.doc Article_Manuscript October_FINAL FINALv2 last version.doc
  31. 31. Slides-RDM-PlanningForRDM-2018-12.ppt Slides-RDM-PlanningForRDM-2018-02.ppt type of document general area of work / topic specific area of work / title date Data collection Naming conventions
  32. 32. • Unencrypted • Uncompressed • Non-proprietary/patent-encumbered • Open, documented standard • Standard representation (ASCII, Unicode) Type Recommended Avoid for data sharing Tabular data CSV, TSV, SPSS portable Excel Text Plain text, HTML, RTF PDF/A only if layout matters Word Media Container: MP4, Ogg Codec: Theora, Dirac, FLAC Quicktime H264 Images TIFF, JPEG2000, PNG GIF, JPG Structured data XML, RDF RDBMS Further examples: http://www.data-archive.ac.uk/create-manage/format/formats-table Data collection File formats
  33. 33. What do others need to understand your data? Embedded documentation • code, field and label descriptions • descriptive headers or summaries • recording information in the Document Properties function of a file (Microsoft) Supporting documentation • Working papers or laboratory books • Questionnaires or interview guides • Final project reports and publications • Catalogue metadata • READ ME file Documentation & metadata Metadata is additional information that is required to make sense of your files – it’s data about data.
  34. 34. Think FAIR! Findable Accessible Interoperable Re-usable The FAIR data principles: https://www.force11.org/group/fairgroup/fairprinciples Documentation & metadata
  35. 35. Guidance on disciplinary metadata standards: http://www.dcc.ac.uk/resources/metadata- standards Documentation & metadata Disciplinary standards
  36. 36. Imagine you have just downloaded the data sample sheet from a repository... 1. What contextual or explanatory information is missing? 2. Is there anything odd about the data that needs clarifying? 3. What additional documentation would you like to see supplied? Documentation & metadata
  37. 37. When working with research participants.... • Ensure you have obtained valid consent • Inform your participants what will happen with the data during and after the project • Consider who needs access to the data • Can data be anonymised • Consider controlling access if anonymisation or consent for sharing are impossible • Pre-planning and agreeing with participants during the consent process, on what may and may not be recorded or transcribed, can be more effective than anonymisation For more information, see the UK Data Archive guidance: https://www.ukdataservice.ac.uk/manage-data/legal-ethical/consent-data-sharing/gaining-consent Ethics & legal compliance Personal and sensitive data
  38. 38. Managing sensitive data • If possible, collect the necessary data without using personally identifying information • There is a difference between pseudonymisation and anonymisation • Pseudonymise or anonymise your data upon collection or as soon as possible thereafter • Avoid transmitting unencrypted personal data electronically • Consider whether you need to keep original collection instruments (recordings, surveys etc.) once they have been transcribed and quality assured Ethics & legal compliance Personal and sensitive data
  39. 39. There are several options available to you: • OU networked file storage • SharePoint • OneDrive • ORDO • Cloud based services (DropBox, Google Drive etc.) Tip: See the comparison guide Storage & backup Storage options
  40. 40. • Shared areas or SharePoint • Zendto • Office 365 has OneDrive • ORDO • Be wary of Dropbox & similar Remember the data storage for research projects comparison table: http://www.open.ac.uk/library-research-support/sites/www.open.ac.uk.library- research-support/files/files/RDM-data-storage-options.pdf Storage & backup External collaborators
  41. 41. Discuss the research data management issues raised by the scenarios. What practical measures could have been taken to reduce risks to security? Photo by Greg Rakozy on unsplash https://unsplash.com/photos/N_3CHNdliVs Storage & backup Information security
  42. 42. Which data should be retained, shared, and/or preserved? • What data must be retained/destroyed for contractual, legal, or regulatory purposes? • How will you decide what other data to keep? • What are the foreseeable research uses for the data? • How long will the data be retained and preserved? Selection & preservation
  43. 43. Rufus Pollock, Cambridge University and Open Knowledge Foundation, 2008 “The coolest thing to do with your data will be thought of by someone else.” Data sharing
  44. 44. Data sharing Why? Funder policies
  45. 45. Since 2017, all Horizon 2020 projects are part of the Open Research Data Pilot by default All publications after May 2015 should have a statement describing how to access underlying data. EPSRC have said they will check. Researchers now required to prepare to share data and other outputs of their work, such as original software and research materials like antibodies, cell lines or reagents. Data sharing Why? Funder policies
  46. 46. Data sharing Why? Publisher policies
  47. 47. “In keeping with OU principles of openness, it is expected that research data will be open and accessible to other researchers, as soon as appropriate and verifiable, subject to the application of appropriate safeguards relating to the sensitivity of the data and legal and commercial requirements.” OU Research Data Management Policy, November 2016 http://www.open.ac.uk/library-research-support/sites/www.open.ac.uk.library- research-support/files/files/Open-University-Research-Data-Management-Policy.pdf Data sharing Why? OU policy
  48. 48. “Good data management is fundamental to all stages of the research process and should be established at the outset.” “Open access to research data is an enabler of high quality research, a facilitator of innovation and safeguards good research practice.” Concordat on Open Research Data http://www.rcuk.ac.uk/documents/documents/concordatonopenresearchdata-pdf/ Data sharing A shared goal
  49. 49. Data sharing Why? Innovation
  50. 50. Data sharing Why? Research integrity
  51. 51. Data sharing Why? More citations
  52. 52. • Raw data • Derived data • Data underpinning publications • Code • Methods What are research data in your context? What would others need to understand your research? Data sharing What do you need to share?
  53. 53. Open Research Data Online (ORDO) Online data sharing services • Figshare • Zenodo • CKAN DataHub • Mendeley Data Directories • re3data Funders’ repository services • UK Data Service ReShare • NERC data centres Data sharing How? Repositories
  54. 54. https://ou.figshare.com ORDO (Open Research Data Online)
  55. 55. Responsibilities & resources Who will be responsible for data management? • Who is responsible for implementing the DMP, and ensuring it is reviewed and revised? • Who will be responsible for each data management activity? • How will responsibilities be split across partner sites in collaborative research projects? What resources will you require to deliver your plan? • Is additional specialist expertise (or training for existing staff) required? • Do you require hardware or software which is additional or exceptional to existing institutional provision? • Will charges be applied by data repositories?
  56. 56. So, there’s a lot to think about… …but there is also a lot of help.
  57. 57. Planning for data Tips • Keep it simple, short and specific • Seek advice - consult and collaborate • Base plans on available skills and support • Make sure implementation is feasible • Justify any resources or restrictions needed
  58. 58. https://dmponline.dcc.ac.uk A web-based tool to help you write DMPs according to different requirements. DCC, funder and OU guidance. Planning for data DMP Online
  59. 59. Library Services How we can help • Data Management Plan checking • Support with setting up new projects • Advice on preparation of data for sharing • Data Repository (ORDO) • Online guidance • Enquiries Email: library-research- support@open.ac.uk
  60. 60. Now for a game… Image: ‘Bingo’ by Jagoba Martínez at https://flic.kr/p/5dwjVt
  61. 61. Rules With thanks to Georgina Parsons: Parsons, Georgina (2017): Writing a DMP - workshop materials. figshare.https://doi.org/10.6084/m9.figshare.5044930.v2Retrieved: 16:00, Aug 15, 2017 (GMT) • Take a bingo card and an example DMP. • Each square contains a positive quality: good DMPs will do all/most of these. • Read each square and if it is true for the example DMP, mark it with a cross. • The first person to get five crosses in a row (vertical, horizontal, or diagonal) calls “Bingo!” and gets a prize.
  62. 62. Useful links • The OU Library Research Support website: http://www.open.ac.uk/library- research-support/research-data-management • Open Research Data Online (ORDO): https://ou.figshare.com • Digital Curation Centre: http://www.dcc.ac.uk/ • DMP Online: https://dmponline.dcc.ac.uk/ • UK Data Archive: http://www.data-archive.ac.uk/ • MANTRA: http://datalib.edina.ac.uk/mantra/ • DataONE: https://www.dataone.org/education-modules • CESSDA: https://www.cessda.eu/Research-Infrastructure/Training/Expert- tour-guide-on-Data-Management • The Orb: http://open.ac.uk/blogs/the_orb • OU Human Research Ethics Committee: http://www.open.ac.uk/research/ethics/ • OU Data Protection: http://intranet6.open.ac.uk/governance/data- protection/advice-and-resources (if clicking on the link doesn’t work, copy and paste the address) • OU Information Security: http://intranet6.open.ac.uk/it/main/information- security (if clicking on the link doesn’t work, copy and paste the address)
  63. 63. Questions?
  64. 64. 3 take home points 1. Start early to help you work better and protect your precious data 2. Write a Data Management Plan 3. Don’t be shy. Ask for help!
  65. 65. Image credits Unless otherwise stated, all images are by Jørgen Stamp at http://www.digitalbevaring.dk

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