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Introduction to r esearch data management

Introduction to r esearch data management. Slides provided by DaMaRO Project, University of Oxford. What Is Research Data Management?. What is data?. “A reinterpretable representation of information in a formalized manner suitable for communication, interpretation, or processing.”

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Introduction to r esearch data management

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  1. Introduction to research data management Slides provided by DaMaRO Project, University of Oxford

  2. What Is Research Data Management? Introduction to research data management

  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. What is data? Any information you use in your research Slide adapted from the PrePARe Project Introduction to research data management

  5. In small groups… • Introduce yourself • 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. What is data management? • Data management is a general term covering how you organize, structure, store, and care for the information used or generated during a research project • It includes: • How you deal with information on a day-to-day basis over the lifetime of a project • What happens to data in the longer term – what you do with it after the project concludes Introduction to research data management

  7. Why spend time and effort on this? • So you can work efficiently and effectively • Save time and reduce frustration • Highlight patterns or connections that might otherwise be missed • Because your data is precious • To enable data re-use and sharing • To meet funders’ and institutional requirements Introduction to research data management

  8. 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

  9. Day-to-Day Data Management Introduction to research data management

  10. 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

  11. Questions to ask • Are you using the most appropriate software or other tools to store and analyse your data? • Do you have a system in place for dealing with new data when you acquire it? • If so, is it realistic? • Are you recording all the necessary contextual information? • Are you using helpful, consistent file naming conventions? Is your file structure clear? Introduction to research data management

  12. 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

  13. File naming strategies – examples • Order by date: 2013-04-12_interview-recording_THD.mp3 2013-04-12_interview-transcript_THD.docx 2012-12-15_interview-recording_MBD.mp3 2012-12-15_interview-transcript_MBD.docx • Order by subject: MBD_interview-recording_2012-12-15.mp3 MBD_interview-transcript_2012-12-15.docx THD_interview-recording_2013-04-12.mp3 THD_interview-transcript_2013-04-12.docx • Order by type: Interview-recording_MBD_2012-12-15.mp3 Interview-recording_THD_2013-04-12.mp3 Interview-transcript_MBD_2012-12-15.docx Interview-transcript_THD_2013-04-12.docx • Forced order with numbering: 01_THD_interview-recording_2013-04-12.mp3 02_THD_interview-transcript_2013-04-12.docx 03_MBD_interview-recording_2012-12-15.mp3 04_MBD_interview-transcript_2012-12-15.docx 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

  14. Keeping your data safe Introduction to research data management

  15. DON’T LET THIS BE YOU! 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

  16. What would happen to your data if there was a fire in your office, department or home? ‘Fire’ by andrewmalone, via Flickr: http://www.flickr.com/photos/andrewmalone/2032844649/ Slide adapted from the PrePARe Project Introduction to research data management

  17. …and keep them in different places Automate the process if you can Slide adapted from the PrePARe Project Introduction to research data management Make multiple copies…

  18. Example back-up plan • Back-up strategy for a recent postdoc research project: • Working data stored on personal laptop • Weekly back-up to external hard drive, and to two memory sticks • Key files also sent as email attachments, or saved to Dropbox • Post-project, data copied to DVDs for long-term storage Introduction to research data management

  19. Think about your storage media… … and about file formats Slide adapted from the PrePARe Project Introduction to research data management

  20. In small groups… • 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

  21. Documentation and metadata Introduction to research data management

  22. Documentation and metadata • Documentation is the contextual information required to make data intelligible and aid interpretation • A users’ guide to your data • Metadata is similar, but usually more structured • Conforms to set standards • Machine readable Introduction to research data management

  23. Make material understandable MAKE SURE YOU CAN UNDERSTAND IT LATER What’s obvious now might not be in a few months, years, decades… 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

  24. Make material verifiable • Detailing your methods helps people understand what you did • And helps make your work reproducible • Conclusions can be verified Image by woodleywonderworks , via Flickr: http://www.flickr.com/photos/wwworks/4588700881/ Slide adapted from the PrePARe Project Introduction to research data management

  25. Make material reusable • You may wish to re-use your own data later on • Or you may wish to make it available for others to use • Provide context to minimize the risk of misunderstanding or misuse • Good metadata makes it easier to locate relevant data Slide adapted from the PrePARe Project Introduction to research data management

  26. 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 ? M. Farinelli et al. (2012) PLoSONE 7(3): e34047 www.texample.net Slide adapted from the PrePARe Project Introduction to research data management

  27. Metadata – data about data • A formal, structured description of a dataset • Used by archives to create catalogue records Introduction to research data management

  28. Missing metadata – or the riddle of the sixth toe • This painting shows Georgiana, Duchess of Devonshire as Diana • … or 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

  29. What Happens at the end of the Project? Introduction to research data management

  30. 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 provides a catalogue: http://databib.org/ • If possible, make it available for others to re-use Introduction to research data management

  31. 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

  32. Why share data? Reuse • Reduces duplication of effort • Allows public research funding to be used more effectively • Contexts not currently envisaged • Extend research beyond your discipline Slide adapted from the PrePARe Project Introduction to research data management

  33. 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 increasinglylooking to publish datasets alongside articles • Be at the forefront of an important shift in the academic world Introduction to research data management

  34. Video by NYU Health Sciences Libraries: http://www.youtube.com/watch?v=N2zK3sAtr-4 Introduction to research data management

  35. Data sharing – concerns • Ethical concerns • Confidential or sensitive data • Legal concerns • Third party data • Professional concerns • Intended publication • Commercial issues (e.g. patent protection) Introduction to research data management

  36. Data sharing – concerns • Redact or embargo if there is good reason • Planning ahead can reduce difficulties EMBARGOED Slide adapted from the PrePARe Project Introduction to research data management

  37. 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

  38. Data licences - examples • Creative Common licences • Widely used and recognized • Six different flavours, plus CC0 public domain dedication • http://creativecommons.org/ • Open Data Commons • Specifically designed for datasets • Recognizes the structure/content distinction • http://opendatacommons.org/ Introduction to research data management

  39. 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

  40. Data Management Planning Introduction to research data management

  41. Data management plans • A document which may be created in the early stages of a project • While planning, applying for funding, or setting up • An 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

  42. 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

  43. 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

  44. ‘In preparing for battle, I have always found that plans are useless but planning is indispensable.’ Dwight D. Eisenhower Introduction to research data management

  45. Further Information and Resources Introduction to research data management

  46. Oxford’s research data management website • An advisory website provided by the University of Oxford • Covers data management planning, back-up and security, data sharing and archiving, funder requirements, etc. • http://www.admin.ox.ac.uk/rdm/ Introduction to research data management

  47. 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

  48. Any questions? Introduction to research data management

  49. 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, 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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