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Introduction to Research Data Management - 2014-02-26 - Mathematical, Physical and Life Sciences Division, University of Oxford

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This slideshow was used in an Introduction to Research Data Management course taught for the Mathematical, Physical and Life Sciences Division, University of Oxford, on 2014-02-26. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.

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Introduction to Research Data Management - 2014-02-26 - Mathematical, Physical and Life Sciences Division, University of Oxford

  1. 1. Introduction to research data management Slides provided by the Research Support Team, IT Services, University of Oxford
  2. 2. WHAT IS RESEARCH DATA MANAGEMENT? Introduction to research data management
  3. 3. What is data? “A reinterpretable representation of information in a formalized manner suitable for communication, interpretation, or processing.” Digital Curation Centre Slide adapted from the PrePARe Project Introduction to research data management
  4. 4. What is data? Any information you use in your research Slide adapted from the PrePARe Project Introduction to research data management
  5. 5. Introductions  What sort of data do you use?  Where does it come from?  Are you creating new data?  Are you working with pre-existing data?  Where is your data stored? Introduction to research data management
  6. 6. What is data management?  A general term covering how you organize, structure, store, and care for the information used or generated during a research project  How you deal with information on a day-today basis over the lifetime of a project happens to data in the longer term – what you do with it after the project concludes  What Introduction to research data management
  7. 7. Carrots and sticks  Work efficiently and  University of Oxford with minimum hassle Policy on the now Management of Research Data and  Save time and avoid problems in the future Records  Make it easy to share  Funding body requirements your data Introduction to research data management
  8. 8. University of Oxford policy Introduced July 2012 Introduction to research data management
  9. 9. University of Oxford policy    The full policy can be viewed on the University of Oxford Research Data Management website Research data defined as the information needed „to support or validate a research project‟s observations, findings or outputs‟ Research data should be:  Accurate, complete, identifiable, retrievable, and securely stored  Able to be made available to others Introduction to research data management
  10. 10. University of Oxford policy  Research data should be retained for „as long as they are of continuing value to the researcher and the wider research community‟ – but a minimum of three years   Specific requirements from funders take precedence Researchers are responsible for:   Planning for the ongoing custodianship of their data   Developing and documenting clear data management procedures Ensuring that legal, ethical, and funding body requirements are met Policy applies to University staff and doctoral students  Depositing relevant research data may ultimately become a condition of award for doctorates Introduction to research data management
  11. 11. Funders‟ requirements  Funding bodies are taking an increasing interest in what happens to research data  You may be required to make your data publicly available at the end of a project  Check the small print in your grant conditions  Many funders require a data management plan as part of grant applications  Oxford‟s RDM website provides a summary of requirements Introduction to research data management
  12. 12. DAY-TO-DAY DATA MANAGEMENT Introduction to research data management
  13. 13. Can you find what you need, when you need it? „What a mess‟ by .pst, via Flickr: http://www.flickr.com/photos/psteichen/3915657914/. Introduction to research data management
  14. 14. Hierarchical systems vs. tagging  Hierarchical organization uses nested folders   Default option for most operating systems Tagging allows more flexibility   Some operating systems support tagging   Items can be in multiple categories File tagging software is also available Sort… or search? Introduction to research data management
  15. 15. Adding tags in Windows 7 Introduction to research data management
  16. 16. Hyperlinks and shortcuts   Hyperlinks are not just for websites – they can also lead to other files on your computer Use shortcuts to avoid duplicating files  Create project folders as an easy way to access related material Introduction to research data management
  17. 17. File naming  Aim for concise but informative names  Ideally, you should be able to tell what‟s in a file without opening it  Think about the ordering of elements within a filename  YYYY-MM-DD dates allow chronological sorting  You can force an order by adding a number at the beginning of the name  Consider including version information Introduction to research data management
  18. 18. File naming strategies – examples  Order by date:  Order by type: 2013-04-12_analysis_ASPH.xlsx 2013-04-12_raw-data_ASPH.txt Analysis_JARID1A_2013-04-12.xlsx 2012-12-15_analysis_JARID1A.xlsx Raw-data_ASPH_2012-12-15.txt 2012-12-15_raw-data_JARID1A.txt  Analysis_ASPH_2012-12-15.xlsx Raw-data_JARID1A_2013-04-12.txt Order by subject:  Forced order with numbering: ASPH_analysis_2012-12-15.xlsx 01_JARID1A_raw-data_2013-04-12.txt ASPH_raw-data_2012-12-15.txt 02_JARID1A_analysis_2013-04-12.xlsx JARID1A_analysis_2013-04-12.xlsx 03_ASPH_raw-data_2012-12-15.txt JARID1A_raw-data_2013-04-12.txt 04_ASPH_analysis_2012-12-15.xlsx Introduction to research data management
  19. 19. File naming strategies – examples In retrospect I am not very happy with the method I used for naming files. The biggest problem was with the newspaper articles I downloaded… I named the files only based on the topic of the article, without mentioning the name of the periodical and the year of publication, which would have been very useful later, when I began writing the thesis. – Doctoral student researching communication history Introduction to research data management
  20. 20. Are you using the right tools for the job?  Take time to assess whether your current software and methods are meeting your needs  Sticking with old familiars can be false economy  Ask friends and colleagues for recommendations Introduction to research data management
  21. 21. Research Skills Toolkit  Website and handson workshops  A guide to software, University services, and other tools and resources for research  Requires SSO login http://www.skillstoolkit.ox.ac.uk/ Introduction to research data management
  22. 22. IT Learning Programme  Over 200 different IT courses  Covering software, skills, and new technologies http://www.oucs.ox.ac.uk/itlp/  ITLP Portfolio offers course materials and other resources http://portfolio.it.ox.ac.uk/ Introduction to research data management
  23. 23. ORDS – Online Research Database Service  Specifically designed for academic research data  Cloud-hosted and automatically backed up  Web interface makes collaboration straightforward  If desired, databases can easily be made public  Designed to permit easy archiving  Currently being used by a small group of test users – will become more widely available later in 2014  http://ords.ox.ac.uk/ Introduction to research data management
  24. 24. KEEPING YOUR DATA SAFE Introduction to research data management
  25. 25. Backing up is easier than replacing lost data… http://blogs.ch.cam.ac.uk/pmr/2011/08/01/why-you-need-a-data-management-plan/ Slide adapted from the PrePARe Project Introduction to research data management
  26. 26. Make multiple copies… …and keep them in different places Automate the process if you can Slide adapted from the PrePARe Project Introduction to research data management
  27. 27. Example back-up plan     Raw data from instruments are stored on the instrument PC, which is backed up every couple of months to DVDs Much raw data also transferred to desktop computers – usually stored on external hard drives Analysed data (e.g. Excel spreadsheets and PowerPoint files) are stored in a shared folder on a departmental server which is backed up daily Lab books are stored inside the laboratory in locked cupboards Introduction to research data management
  28. 28. IT Services: Data Back-up on the HFS HFS is Oxford‟s central back-up and archiving service  Free of charge to University staff and postgraduates  Automated back-ups of machines connected to University network  Copies kept in multiple places  Introduction to research data management
  29. 29. Think about your storage media… … and about file formats Slide adapted from the PrePARe Project Introduction to research data management
  30. 30. For discussion  What data management challenges have you encountered?  What strategies have you personally found useful?  Be ready to feed back to the group Introduction to research data management
  31. 31. DOCUMENTATION AND METADATA Introduction to research data management
  32. 32. Documentation and metadata  Documentation is the contextual information required to make data intelligible and aid interpretation A users‟ guide to your data  May  be given at study level or data level Metadata is similar, but usually more structured  Conforms  Machine to set standards readable Introduction to research data management
  33. 33. Make material understandable What‟s obvious now might not be in a few months, years, decades… MAKE SURE YOU CAN UNDERSTAND IT LATER Adapted from „Clay Tablets with Linear B Script‟ by Dennis, via Flickr: http://www.flickr.com/photos/archer10/5692813531/ Slide adapted from the PrePARe Project Introduction to research data management
  34. 34. Make material verifiable Image by woodleywonderworks , via Flickr: http://www.flickr.com/photos/wwworks/4588700881/ • Detailing your methods helps people understand what you did • Reduces risk of misinterpretation • Helps make your work reproducible • Conclusions can be verified Slide adapted from the PrePARe Project Introduction to research data management
  35. 35. Introduction to research data management
  36. 36. Exercise  In small groups, look at the sample data sheet  Imagine you have just downloaded this dataset from an archive  What contextual or explanatory information is missing?  What additional documentation would you like to see supplied  At the data level?  At the study level? Introduction to research data management
  37. 37. Documentation – what to include • Who created it, when and why • • • • Description of the item Methodology and methods Units of measurement Definitions of jargon, acronyms and code • References to related data Slide adapted from the PrePARe Project Introduction to research data management
  38. 38. Metadata – data about data  A formal, structured description of a dataset  Used by archives to create catalogue records Introduction to research data management
  39. 39. ISA tools software suite Open source metadata tracking tools for the life sciences http://isa-tools.org/ Introduction to research data management
  40. 40. Missing metadata – or the riddle of the sixth toe    This painting shows Georgiana, Duchess of Devonshire as Diana … or maybe Cynthia She has six toes – but no one knows why Public domain image from Wikimedia Commons: http://commons.wikimedia.org/wiki/File:Georgiana_Cavendish,_Duchess_of_Devonshire_as_Diana.jpg Introduction to research data management
  41. 41. WHAT HAPPENS AT THE END OF THE PROJECT? Introduction to research data management
  42. 42. Data archiving  Data generated during a research project is valuable  Don‟t leave it languishing on your hard drive  Consider depositing it in an archive or repository A number of national disciplinary archives exist  DataBib  Oxford  provides a catalogue: http://databib.org/ will soon have its own data archive If possible, make it available for others to re-use Introduction to research data management
  43. 43. Why share data? Reputation  Get credit for high quality research  Recognition for contribution to research community  Open data leads to increased citations  Of the data itself  Of associated papers Slide adapted from the PrePARe Project Introduction to research data management
  44. 44. Why share data? Reuse  Reduces duplication of effort  Allows public research funding to be used more effectively  Extend research beyond your discipline  Perhaps into contexts not currently envisaged Slide adapted from the PrePARe Project Introduction to research data management
  45. 45. Why share data? Be a trailblazer!  A paradigm shift in how research outputs are viewed is occurring  Data outputs are of increasing importance – and are likely to become even more so   Major journals are increasingly looking to publish datasets alongside articles Be at the forefront of an important shift in the academic world Introduction to research data management
  46. 46. Figshare  Free online data sharing platform   Shared research is allocated a DataCite DOI A possible alternative to conventional repositories  If no suitable repository is available  If you need a data sharing solution in a hurry Introduction to research data management
  47. 47. Video by NYU Health Sciences Libraries: http://www.youtube.com/watch?v=N2zK3sAtr-4 Introduction to research data management
  48. 48. Data sharing – concerns  Ethical concerns  Confidential  Legal concerns  Third  or sensitive data party data Professional concerns  Intended publication  Commercial issues (e.g. patent protection) Introduction to research data management
  49. 49. Data sharing – concerns • Redact or embargo if there is good reason • Planning ahead can reduce difficulties Slide adapted from the PrePARe Project Introduction to research data management
  50. 50. Data licensing  A licence clarifies the conditions for accessing and making use of a dataset  User knows what‟s allowed without asking further permission  Doesn‟t exclude possibility of specific requests to go beyond the terms of the licence  For databases, structure and content may be covered by separate rights Introduction to research data management
  51. 51. Data licences - examples  Creative Common licences   Six different flavours, plus CC0 public domain dedication   Widely used and recognized http://creativecommons.org/ Open Data Commons  Specifically designed for datasets  Recognizes the structure/content distinction  http://opendatacommons.org/ Introduction to research data management
  52. 52. Data licensing - guidance  „How to License Research Data‟ A guide from the Digital Curation Centre http://www.dcc.ac.uk/resources/how-guides/license-research-data Introduction to research data management
  53. 53. DATA MANAGEMENT PLANNING Introduction to research data management
  54. 54. Data management plans  A document which may be created in the early stages of a project  While  An  planning, applying for funding, or setting up initial plan may be expanded later Details plans and expectations for data  Nature of data and its creation or acquisition  Storage and security  Preservation and sharing Introduction to research data management
  55. 55. Exercise  Using the resources available, have a go at drafting a data management plan for your own research  If there are questions you can‟t answer at this stage, make a note of  What you need to find out  Decisions you need to make Introduction to research data management
  56. 56. Digital Curation Centre  A national service providing advice and resources  Create a data management plan using the DMP online tool http://www.dcc.ac.uk/ https://dmponline.dcc.ac.uk/ Introduction to research data management
  57. 57. „In preparing for battle, I have always found that plans are useless but planning is indispensable.‟ Dwight D. Eisenhower Introduction to research data management
  58. 58. UNIVERSITY SERVICES Introduction to research data management
  59. 59. ORA-Data and DataFinder   Two forthcoming University of Oxford services Launch date TBC Introduction to research data management
  60. 60. ORA-Data (formerly DataBank)   University of Oxford‟s institutional data archive Long term preservation for datasets without another natural home    Datasets will be assigned DOIs Will work alongside ORA-Publications to form a composite University archive   In some cases, may a suitable home for DPhil data Possible to link publications and datasets in ORA Depositors can opt to make datasets publicly available, embargoed for a fixed period, or hidden Introduction to research data management
  61. 61. DataFinder  A catalogue of datasets   Will harvest metadata from ORA-Data and other compatible data stores    Information on the nature, location, and availability of the data So anything in ORA-Data will have a record in DataFinder Researchers depositing data elsewhere strongly encouraged to add a record to DataFinder Should provide a substantial resource for researchers seeking datasets for reuse Introduction to research data management
  62. 62. FURTHER INFORMATION AND RESOURCES Introduction to research data management
  63. 63. Research data management website Oxford‟s central advisory website  University policy is available  Questions? Email researchdata @ox.ac.uk  http://researchdata.ox.ac.uk/ Introduction to research data management
  64. 64. IT Services: Research Support Team  Can assist with technical aspects of research projects at all stages of the project lifecycle  Help  But  with DMPs, selecting software or storage, etc. the earlier you seek advice, the better For more information, see our website: http://research.it.ox.ac.uk Introduction to research data management
  65. 65. Research Data MANTRA  Free online interactive training modules  Aimed at postgraduates and early career researchers http://datalib.edina.ac.uk/mantra/ Introduction to research data management
  66. 66. Any questions? Ask now, or email us on researchdata@ox.ac.uk Introduction to research data management
  67. 67. Rights and re-use     This slideshow is part of a series of research data management training resources prepared by the DaMaRO Project at the University of Oxford With the exception of clip art used with permission from Microsoft, commercial logos and trademarks, and images credited to other sources, the slideshow is made available under a Creative Commons Attribution Non-Commercial Share-Alike License Parts of this slideshow draw on teaching materials produced by the PrePARe Project, DATUM for Health, and DataTrain Archaeology Within the terms of this licence, we actively encourage sharing, adaptation, and re-use of this material Introduction to research data management

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