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Natasha intro to rdm c3 dis may 2018.pptx

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Introduction to research data management. Presented by Natasha Simons at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management, Melbourne 31st may 2018

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Natasha intro to rdm c3 dis may 2018.pptx

  1. 1. Natasha Simons Introduction to Research Data Management (RDM) 31 May 2018 C3DIS, Melbourne
  2. 2. Today’s workshop Introduction to research data management – Natasha Simons Making your data FAIR (Findable, Accessible, Interoperable and Reusable): standards for describing and publishing data, linking data to other research outputs, supporting machine readability of data and licensing your data – Carmi Cronje and Anne Stevenson 10.30am morning tea break How to manage your ‘working data’: data storage infrastructure, backup, file naming and sharing - John Morrissey Managing personal and sensitive data – Natasha Simons Data Management Plans – Sue Cook
  3. 3. What is Research Data? Research data means: data in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test or hypothesis, or another research output is based. Data may be numerical, descriptive, visual or tactile. It may be raw, cleaned or processed, and may be held in any format or media. But this is only one definition of many…. Photo by rawpixel on Unsplash
  4. 4. What is Research Data? Any definition of research data is likely to depend on the context in which the question is asked. http://www.ands.org.au/guides/what-is-research-data Photo by h heyerlein on Unsplash
  5. 5. What data do you collect/work with? Photo by Jonatan Pie on Unsplash
  6. 6. What’s Research Data Management? Research Data Management covers the planning, collecting, organising, managing, storage, security, backing up, preserving, and sharing your data. It ensures that research data are managed according to legal, statutory, ethical and funding body requirements. Source: UQ LibGuide Any research will require some level of data management. Photo by imgix on Unsplash
  7. 7. Why should you care about RDM? Good data management can: • Increase the efficiency of your research • Help guarantee the quality and authenticity of your data • Enable the exposure of your research outcomes through collaboration and dissemination • Provide for the reproducibility of experimental and computational outcomes • Facilitate the validation and verification of results. Photo by Jaron Nix on Unsplash
  8. 8. More publishers require data A condition of publication in a Nature journal is that authors are required to make materials, data, code, and associated protocols promptly available to readers without undue qualifications.
  9. 9. More funders require data “We want the research we fund – like publications, data, software and materials – to be open and accessible, so it can have the greatest possible impact” – Wellcome Trust https://wellcome.ac.uk/what-we-do/topics/data-sharing NHMRC’s Australian Code for the Responsible Conduct of Research: includes the proper management and retention of the research data. Australian Research Council (ARC) application forms (Discovery; Linkage) have a short section where you are required to provide an outline of your data management plan. ANDS Guide: ARC applications – filling in the data management sectionhttp://www.ands.org.au/guides/arc-guide-to-filling-in-the-dm-section
  10. 10. More government policies on data The main purpose of the site is to encourage public access to and reuse of public data. It was created following the Government’s Declaration of Open Government and as a response to the Government 2.0 Taskforce Report.
  11. 11. More institutional policies on data The University of Sydney RDM Policy - http://sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2013/337&RendNum=0 - and RDM Procedures - http://sydney.edu.au/policies/showdoc.aspx?recnum=PDOC2014/366
  12. 12. More researchers care about data sharing Figshare open data survey of researchers 2017: • 82% aware of open data sets • 80% willing to reuse open data sets in own research • 60% routinely share their data (frequently or sometimes) • 21% have never made a data set openly available • 74% are now curating their data for sharing • 77% value a data citation the same as an article Science, Digital (2017): The State of Open Data 2017 Report - Infographic. figshare.https://doi.org/10.6084/m9.figshare.5519155.v1 pp. 7-11
  13. 13. More researchers are sharing their data More than two thirds of Wiley researchers reported they are now sharing their data. Though this varies geographically and across research disciplines we are seeing that more researchers are sharing their data and taking efforts to make it reproducible. Wiley Global Data Sharing Infographic June 2017. https://authorservices.wiley.co m/author-resources/Journal-A uthors/licensing-open-access/o pen-access/data-sharing.html
  14. 14. Data sharing models https://vimeo.com/125783029
  15. 15. Key messages • Any definition of research data is likely to depend on the context in which the question is asked. • Any research will require some level of data management. • Good data management can increase the efficiency of your research and enable the exposure of your research outcomes through collaboration and dissemination • More publishers, funders, governments and institutions require data management and sharing • More researchers care about data sharing and are sharing their own data • Data sharing models can be open/shared/closed
  16. 16. Program Leader, Skills, Policy and Resources natasha.simons@ands.org.au @n_simons Natasha Simons With the exception of third party images or where otherwise indicated, this work is licensed under the Creative Commons 4.0 International Attribution Licence. ANDS, Nectar and RDS are supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program (NCRIS).

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