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Practical Strategies for Research Data Management

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Slides from a workshop delivered on 5th November 2018 for OU researchers.

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Practical Strategies for Research Data Management

  1. 1. Practical Strategies for Research Data Management 5th November 2018 Dan Crane, Research Support Librarian library-research-support@open.ac.uk
  2. 2. 2 http://www.open.ac.uk/library-research-support/
  3. 3. 3 What is Research Data Management? Planning for data management Useful resources Questions (and feedback) WHAT WE’LL COVER 01 02 03 04 • Data collection • Documentation and metadata • Ethics and legal • Storage and backup • Selection and preservation • Data sharing • Responsibilities and resources
  4. 4. 4 Aims of the session: • Know what RDM is • Be aware of some of the drivers and benefits • What a Data Management Plan (DMP) is • How to approach some of the key aspects of data management • Where to go for more information
  5. 5. 5 But first… …introductions
  6. 6. 6 …and, what do you want to get out of the session?
  7. 7. WHAT IS RDM?
  8. 8. 8 WHAT IS RESEARCH DATA MANAGEMENT? Research data is defined as the evidence base on which academic researchers build their analytic or other work. Such data may be in any form, but may include “digital information created directly from research activities such as experiments, analysis, surveys, measurements, instrumentation and observations; data resulting from automated or manual data reduction and analysis including the inputs and outputs of simulations and models” RCUK / UKRI Common principles on data policy WHAT DO WE MEAN BY ‘DATA’ Open University Research Data Management Policy
  9. 9. 9 Research data are the evidence that underpins the answer to the research question, and can be used to validate findings regardless of its form (e.g. print, digital, or physical). These might be quantitative information or qualitative statements collected by researchers in the course of their work by experimentation, observation, modelling, interview or other methods, or information derived from existing evidence. Data may be raw or primary (e.g. direct from measurement or collection) or derived from primary data for subsequent analysis or interpretation (e.g. cleaned up or as an extract from a larger data set), or derived from existing sources where the rights may be held by others. Data may be defined as ‘relational’ or ‘functional’ components of research, thus signalling that their identification and value lies in whether and how researchers use them as evidence for claims. They may include, for example, statistics, collections of digital images, sound recordings, transcripts of interviews, survey data and fieldwork observations with appropriate annotations, an interpretation, an artwork, archives, found objects, published texts or a manuscript. WHAT IS RESEARCH DATA MANAGEMENT? WHAT DO WE MEAN BY ‘DATA’ Concordat on Open Research Data https://www.ukri.org/files/legacy/documents/concordatonopenresearchdata-pdf/
  10. 10. 10 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
  11. 11. 11 UK Data Archive Data Lifecycle model WHAT IS RESEARCH DATA MANAGEMENT? Design research Plan data management Plan consent for sharing Locate existing data Collect data Capture and create metadata Creating data http://www.data-archive.ac.uk/create-manage/life-cycle
  12. 12. 12 UK Data Archive Data Lifecycle model WHAT IS RESEARCH DATA MANAGEMENT? Enter data, digitise, transcribe, translate Check, validate, clean data Anonymise data Describe data Manage and store data Processing data http://www.data-archive.ac.uk/create-manage/life-cycle
  13. 13. 13 UK Data Archive Data Lifecycle model WHAT IS RESEARCH DATA MANAGEMENT? Interpret data Produce research outputs Author publications Prepare data for publications Analysing data http://www.data-archive.ac.uk/create-manage/life-cycle
  14. 14. 14 UK Data Archive Data Lifecycle model WHAT IS RESEARCH DATA MANAGEMENT? Migrate data to best format Migrate data to suitable medium Back-up and store data Create metadata and documentation Archive data Preserving data http://www.data-archive.ac.uk/create-manage/life-cycle
  15. 15. 15 UK Data Archive Data Lifecycle model WHAT IS RESEARCH DATA MANAGEMENT? Distribute data Share data Control access Establish copyright Assign licences Promote data Giving access to data http://www.data-archive.ac.uk/create-manage/life-cycle
  16. 16. 16 UK Data Archive Data Lifecycle model WHAT IS RESEARCH DATA MANAGEMENT? Follow-up research New research Undertake research reviews Scrutinise findings Teach and learn Re-using data http://www.data-archive.ac.uk/create-manage/life-cycle
  17. 17. 17 Why spend time and effort on this? WHAT IS RESEARCH DATA MANAGEMENT? • So you can work efficiently and effectively - save time and reduce frustration • Because your data is precious • To enable data re-use and sharing • To meet funders’ and institutional requirements
  18. 18. 18 What does the OU expect? WHAT IS RESEARCH DATA MANAGEMENT? “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
  19. 19. 19 What do funders expect? WHAT IS RESEARCH DATA MANAGEMENT? Concordat on Open Research Data https://www.ukri.org/files/legacy/documents/concordatonopenresearchdata-pdf/ “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.”
  20. 20. 20 What does the OU provide? WHAT IS RESEARCH DATA MANAGEMENT? • Support from the library research support team and website library-research-support@open.ac.uk http://www.open.ac.uk/library-research-support/
  21. 21. 21 What does the OU provide? WHAT IS RESEARCH DATA MANAGEMENT? • A research data repository, (ORDO) for secure, long-term storage of data, meeting funder requirements https://ou.figshare.com/
  22. 22. 22 Discussion WHAT IS RESEARCH DATA MANAGEMENT? • What type of data do you create/use? • What data management challenges do you face? For 5 minutes
  23. 23. PLANNING FOR DATA MANAGEMENT
  24. 24. 24 “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. Finish PLANNING FOR DATA MANAGEMENT
  25. 25. 25 The Data Management Plan PLANNING FOR DATA MANAGEMENT a project document that describes: • the data that a project will collect • how data will be stored, transferred, backed up during the project • how data will be archived at the end of the project • how access will be granted to data where appropriate Data Management Plans What are they?
  26. 26. 26 The Data Management Plan PLANNING FOR DATA MANAGEMENT • Make informed decisions to anticipate and avoid problems • Develop procedures early on for consistency • Avoid duplication, data loss and security breaches • Tell your funder that you know what you are doing (and get funding!) • Save time and effort – make your life easier! Data Management Plans Why write one?
  27. 27. 27 The Data Management Plan PLANNING FOR DATA MANAGEMENT • As soon as possible • When submitting funding bids • But if you’re not applying for funding, do one too • Update it during your work Data Management Plans When do I need to do one?
  28. 28. 28 The Data Management Plan PLANNING FOR DATA MANAGEMENT Data Collection What data will you collect or create? How will the data be collected or created?
  29. 29. 29 The Data Management Plan PLANNING FOR DATA MANAGEMENT Data Collection What data will you collect or create? How will the data be collected or created? Documentation and Metadata What documentation and metadata will accompany the data?
  30. 30. 30 The Data Management Plan PLANNING FOR DATA MANAGEMENT Data Collection What data will you collect or create? How will the data be collected or created? 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?
  31. 31. 31 The Data Management Plan PLANNING FOR DATA MANAGEMENT Storage and Backup How will the data be stored and backed up during the research? How will you manage access and security?
  32. 32. 32 The Data Management Plan PLANNING FOR DATA MANAGEMENT Storage and Backup How will the data be stored and backed up during the research? How will you manage access and security? Selection and Preservation Which data should be retained, shared, and/or preserved? What is the long-term preservation plan for the dataset?
  33. 33. 33 The Data Management Plan PLANNING FOR DATA MANAGEMENT Storage and Backup How will the data be stored and backed up during the research? How will you manage access and security? 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?
  34. 34. 34 The Data Management Plan PLANNING FOR DATA MANAGEMENT Storage and Backup How will the data be stored and backed up during the research? How will you manage access and security? 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?
  35. 35. Data collection
  36. 36. 36 The basics Data collection • What data will I have? • How many files? • How big will they be? • What format(s) will I use? • How will it be collected? • How will it be organised?
  37. 37. 37 Organising your data Data collection 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.
  38. 38. 38 File naming Data collection 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.
  39. 39. 39 File naming: an example Data collection Slides-RDM-PracticalStrategiesForRDM-2018-11.ppt Slides-RDM-PracticalStrategiesForRDM-2018-11.ppt type of document general area of work / topic specific area of work / title date
  40. 40. 40 File naming: what to avoid… Data collection 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
  41. 41. 41 Folder structure Data collection An example: by Nikola Vukovic : http://nikola.me/folder_structure.html
  42. 42. Documentation and metadata
  43. 43. 43 Documentation and metadata What do others need to understand your data? Metadata is additional information that is required to make sense of your files – it’s data about data. Project level 1. For what purpose was data created 2. What does the dataset contain 3. How was data collected 4. Who collected the data and when 5. How was the data processed 6. What possible manipulations were done to the data 7. What were the quality assurance procedures 8. How can data be accessed CESSDA ERIC: https://www.cessda.eu/Research-Infrastructure/Training/Expert-Tour-Guide-on-Data-Management Supporting documentation • Working papers or laboratory books • Questionnaires or interview guides • Final project reports and publications • Catalogue metadata • READ ME file
  44. 44. 44 Documentation and metadata 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) Metadata is additional information that is required to make sense of your files – it’s data about data. Object level CESSDA ERIC: https://www.cessda.eu/Research-Infrastructure/Training/Expert-Tour-Guide-on-Data-Management
  45. 45. 45 Documentation and metadata Guidance on disciplinary metadata standards: http://www.dcc.ac.uk/resources/metadata-standards Disciplinary standards
  46. 46. 46 Documentation and metadata 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 metadata would you like to see supplied? Discussion
  47. 47. Ethics and legal
  48. 48. 48 Personal and sensitive data Ethics and legal • Legal: See ‘OU Data protection procedures’ and start with the DPIA screening questions Link to intranet (requires log-in) http://intranet6.open.ac.uk/governance/data-protection/ Working with personal data? • Ethical: See Human Research ethics guidance and the ‘HREC Project Registration and Risk Checklist’ Link to website http://www.open.ac.uk/research/ethics/human-research
  49. 49. 49 Personal and sensitive data Ethics and legal When working with research participants.... • Inform your participants what will happen with the data during and after the project • Ensure you have obtained their consent • Consider who needs access to the data • Can data be anonymised or pseudonymised? • 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 Service guidance: https://www.ukdataservice.ac.uk/manage-data/legal-ethical/consent-data-sharing/gaining-consent
  50. 50. 50 Personal and sensitive data Ethics and legal 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.
  51. 51. 51 Personal and sensitive data Ethics and legal Other issues: • Copyright – of your data and any you re-use • Collaborations
  52. 52. Storage and backup
  53. 53. 53 Data storage and security Storage and backup • Data size, complexity • Where will you be working, collecting and accessing your data? • Are you working with anyone?
  54. 54. 54 Data storage and security Storage and backup There are several storage options available to you: • OU networked file storage • OneDrive • SharePoint • STEM Specialist Support Unit • ORDO • Cloud based services (DropBox, Google Drive etc.) Tip: See the comparison guide
  55. 55. 55 Data storage and security - collaboration Storage and backup • OneDrive • SharePoint • ORDO • Zendto (for one-off transfers) • Be wary of Dropbox & similar
  56. 56. Selection and preservation
  57. 57. 57 Data storage and security Selection and preservation What data should be retained, preserved and shared? • 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?
  58. 58. Data sharing
  59. 59. 59 A quick overview Data sharing • Supporting publication or end of project • In a trusted repository • With metadata • As open as possible​ • Available for 10 years​ • Discoverable, accessible, citeable • With a licence • Data access statement in publications “Researchers will, wherever possible, make their research data open and usable within a short and well defined period, which may vary by subject and disciplinary area and reflect the resources available to them to do so. Data supporting publications should be accessible by the publication date and should be in a citeable form“ Concordat on Open Research Data https://www.ukri.org/files/legacy/documents/concordatonopenresearchdata-pdf/
  60. 60. 60 A quick overview Data sharing • Benefits: transparency, re-use, impact • Required by many funders and publishers • Lots of tools and guidance to help researchers • Come to our session on 27 Nov ‘Making your research data open’ or see our online training sessions and recordings: • ‘Data sharing: how, what and why?’ Online / Recording • ‘Data sharing: legal and ethical issues’ Online / Recording
  61. 61. Responsibilities and resources
  62. 62. 62 Responsibilities and 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?
  63. 63. 63 The Data Management Plan PLANNING FOR DATA MANAGEMENT So, there’s a lot to think about…
  64. 64. 64 How we can help PLANNING FOR DATA MANAGEMENT • Data Management Plan checking • Support with setting up new projects • Advice on preparation of data for sharing • Data Repository (ORDO) • Online guidance • Enquiries
  65. 65. 65 Tips PLANNING FOR DATA MANAGEMENT • 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
  66. 66. 66 Activity PLANNING FOR DATA MANAGEMENT Think about your own research. Have a go at writing your own DMP…
  67. 67. 67 DMP Online PLANNING FOR DATA MANAGEMENT https://dmponline.dcc.ac.uk • A web-based tool to help you write DMPs according to different requirements. • DCC, funder and OU guidance.
  68. 68. 68 Now for a game… PLANNING FOR DATA MANAGEMENT Image:‘Bingo’byJagobaMartínezathttps://flic.kr/p/5dwjVt
  69. 69. 69 Now for a game… PLANNING FOR DATA MANAGEMENT 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.
  70. 70. USEFUL RESOURCES
  71. 71. 71 Links USEFUL RESOURCES • 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/ • CESSDA ERIC training: 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)
  72. 72. QUESTIONS?
  73. 73. 73 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!
  74. 74. 74 FEEDBACK How did we do? Before you go, please fill out our very short feedback form to tell us: • One thing you liked about today's session • One thing you would change Use the paper form, or online form at: https://bit.ly/2EZu0K6
  75. 75. THANK YOU
  76. 76. 76 IMAGE CREDITS Unless otherwise stated, all images are by Jørgen Stamp at http://www.digitalbevaring.dk

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