Research Data Management in practice, RIA Data Management Workshop Brisbane 2017
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The Australian National Data Service (ANDS) aims to make Australian research data more valuable by partnering with research organizations and funding data projects. In 2015, ANDS conducted over 100 workshops and events with over 4,000 participants and developed online resources. ANDS provides guides on topics like data management and the FAIR data principles. ANDS also advocates for practices like data citation and publishing to ensure research data is preserved and reusable over time. The presentation outlines ANDS' role in supporting good research data management practices and sharing to ensure the integrity and impact of research evidence.
![Ethics Clearance and Data Access: A Case Study
Data Managing and Sharing Research Data: A Guide to Good Practice, SAGE 2014
https://uk.sagepub.com/en-gb/eur/managing-and-sharing-research-
data/book240297
https://commons.wikimedia.org/wiki/File%3AFoot_and_Mouth_Disease_Map_-_geograph.org.uk_-_564718.jpg
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Research Data Management in practice, RIA Data Management Workshop Brisbane 2017
- 1. Dr Paul Wong Research Integrity Advisor Data Management Workshop Senior Data Management Specialist 31 March 2017 Brisbane QUT
- 2. The Australian National Data Service (ANDS) makes Australia’s research data assets more valuable for researchers, research institutions and the nation. Partnering Australian research organisations and co-funded 294 data projects, totally $54M Research Data Australia Cite My Data / DOIs minting Vocabulary service etc. In 2015, conducted over 100 workshops, forums, and webinars with over 4000 participants, developed online resources e.g. guides, videos etc.
- 3. • 40+ guides organised around different topics • Content is a moving target – changing policy landscape, new practices etc. • Designed as a community resource • If you see gaps, we want your help to make them better http://www.ands.org.au/guides
- 4. • A dedicated set of webpages on data management • A community resource • If you see gaps, we want your help to make them better http://www.ands.org.au/working-with-data/data-management
- 6. Research data: as input & output Research data may include: Laboratory and field notes Raw experimental data Analysed data Simulations and software Databases Clinical data, including clinical records Questionnaires/surveys Images and photographs Audio-visual materials Moynihan's field notes, Panama, 1958 – CC BY https://flic.kr/p/dmXHkJ Screen capture of “Computer simulation of March 22, 2014 landslide event near Oso, Washington, by David L. George and Richard M. Iverson, USGS” http://youtu.be/2NzHCOhKr7g CC BY
- 7. Creative arts research data Research data in the creative arts may include: Audio-visual recordings of a creative work Visual diaries Journals Drawings Photographs Manuscripts Musical annotations 3D models
- 8. Research Data: a Broad Church Hand written letters Images or photos Soil samples Tissue samples Archeological dig sites ….. Scanned & OCR version Scanned digital version Analysed result of samples Analysed result of samples 3D models of the dig site ….. Physical Digital ANDS’ primary focus is digital data
- 9. Why Bother? Why managing (digital) research data? In fact, why bother managing anything? • Prevent bad things from happening. • Enable good things to happen.
- 10. Data and Research Integrity Nature 533, 452–454 (26 May 2016) doi:10.1038/533452a. Reprint with permission © 2016 Macmillan
- 11. Data and Research Integrity “The Availability of Research Data Declines Rapidly with Article Age”, Vine et al, Current Biology, Volume 24, Issue 1, p94–97, 6 January 2014 • “For papers where authors reported the status of their data, the odds of the data being extant decreased by 17% per year...” • “Responses included authors being sure that the data were lost (e.g., on a stolen computer) or thinking that they might be stored in some distant location (e.g., their parent’s attic) to authors having some degree of certainty that the data are on a Zip or floppy disk in their possession but no longer having the appropriate hardware to access it.”
- 12. Make Data Awesome Open Research Data Collection Showcase http://www.ands.org.au/partners-and- communities/projects/open-research-data-collection #Dataimpact stories http://www.ands.org.au/news-and-events/dataimpact The companion case studies report of the Watt review https://docs.education.gov.au/system/files/doc/other/20 151202_case_studies_volume_nc_0.pdf
- 14. Data Management in Practice • One of ANDS’ guides to outline, in an easy to understand practical framework, how research data can be managed effectively in an institutional setting. • 15 key points – with short descriptions, 7 pages long. • Incorporating project management best practice • Shared responsibilities model • Continual data curation approach • Road tested with librarians, data managers, researchers and research support staff
- 15. The Current Thinking: FAIR Findable, Accessible, Interoperable, Reusable 15 principles to ensure research data is FAIR Mark D. Wilkinson et al. The FAIR Guiding Principles for scientific data management and stewardship, Scientific Data (2016). DOI: 10.1038/sdata.2016.18 “FAIRness is a prerequisite for proper data management and data stewardship”
- 17. Continual data curation across domains
- 18. Data Curation as Documentation Assigning metadata (structured data about the data) • Who collected the data? • Who funded the research project? • When (and where) was it collected? • Instruments and setting for collecting the data? • Title of the dataset • Methods used to process the data • Etc. etc.
- 19. Light Touch Heavy Duty Ecological Geographic Biological Metadata Structured Detailed Machine readable Structured Minimal Human readable
- 20. What is Data Citation? Data citation refers to the practice of providing a reference to data in the same way as researchers routinely provide a bibliographic reference to outputs such as journal articles, reports and conference papers. Citing data is now recognised as one of the key practices leading to recognition of data as a primary research output. http://www.ands.org.au/working-with-data/citation-and- identifiers/data-citation
- 21. Data Citation Standard A standard citation would include the following elements: Author(s) (Year): Title. Publisher(s). DOI (if used) Hanigan, Ivan (2012): Monthly drought data for Australia 1890-2008 using the Hutchinson Drought Index. The Australian National University Australian Data Archive. http://doi.org/10.4225/13/50BBFD7E6727A Alternatively, Author(s) (Year): Title. Version. Publisher(s). ResourceType. Identifier Bradford, Matt; Murphy, Helen; Ford, Andrew; Hogan, Dominic; Metcalfe, Dan (2014): CSIRO Permanent Rainforest Plots of North Queensland. v2. CSIRO. Data Collection. http://doi.org/10.4225/08/53C4CC1D94DA0 http://www.ands.org.au/working-with-data/citation-and-identifiers/data-citation
- 22. Institutional Policy and Procedures Support services - people and other means of providing advice and support IT Infrastructure - the hardware, software and other facilities Metadata management - so that data records can be meaningful and fit for purpose Institutional Data Management Framework Pre Research
- 23. Data Management Plan • data organisation and storage; • metadata standards and guidelines; • backups; • archiving for long-term preservation; • version control and derived data products; • data sharing or publishing intentions, including licensing; • ensuring security of confidential data; • data synchronisation; and • governance, roles and responsibilities. Pre Research
- 24. Storage requirements may vary across domains
- 25. Publishing and Sharing Data Metadata Research Data Open Open Open Closed Closed Open Closed Closed Publishing and Sharing data ≠ Open Access to data “Open” and “Closed” are relative concepts. “Closed” ≈ conditional access based on individual permission “Closed” ≈ conditional access based on roles Post Research
- 26. Ethics Clearance and Data Access: A Case Study Data Managing and Sharing Research Data: A Guide to Good Practice, SAGE 2014 https://uk.sagepub.com/en-gb/eur/managing-and-sharing-research- data/book240297 https://commons.wikimedia.org/wiki/File%3AFoot_and_Mouth_Disease_Map_-_geograph.org.uk_-_564718.jpg Colin Smith [CC BY-SA 2.0] (http://creativecommons.org/licenses/by-sa/2.0)], via Wikimedia Commons from Wikimedia Commons)
- 27. Ethics Clearance and Data Access: A Case Study Health and Social Consequences of the Foot and Mouth Disease Epidemic in North Cumbria, 2001- 2003 (M. Mort Lancaster University 2006, funded by the Department of Health UK, Study Number 5407) http://ukdataservice.ac.uk/use-data/guides/dataset/foot-and-mouth http://discover.ukdataservice.ac.uk/catalogue/?sn=5407 • 54 local people were recruited to write weekly diaries over 18 months to describe their lives and the recovery they observed around the area • The study was supplemented with interviews and focus group discussions that included other stakeholders • The study obtained consent from participants before the research but did not get consent for sharing and archiving data • The research team and the Department of Health wanted to share and archive the data after the completion of the research. • Had to get consent retrospectively and needed expert advice from copyright specialists
- 28. http://www.ands.org.au/__data/assets/pdf_file/0009/394056/research-data-management-in-practice.pdf The framework treats DM as a set of coordinated activities to preserve the evidence base of research findings and to make the evidence base more accessible and reusable in the long run.
- 29. Wise Advise https://nicolahemmings.wordpress.com/2016/04/05/mistakes-ive-made-as- an-early-career-researcher/ Mistakes I’ve made as an early career researcher APRIL 5, 2016 Nicola Hemmings (post-doc, University of Sheffield) Failing to organise my data adequately (circa 2007). Prepare your datasets like you would if you were giving them to a stranger who knew nothing about them. Label, annotate and meticulously file your R scripts. Incorporate read-me files into everything and write them for the monkey that will be you in five years, when you return to your data and/or analyses for some unforeseen but vitally important reason. Don’t get this wrong. You will regret it.
- 30. Special Healthy Data Year ‘Sharing health-y data: challenges and solutions’ workshops ANDS ran in all capital cities in 2016-2017 Attended by researchers, and staff from the library, research office and ethics office Topics covered The data sharing landscape: funders and publishers Data de-identification Ethics and informed consent Licensing data How research data can be published (mediated access, metadata, repositories)
- 31. Special Healthy Data Year Coming up: Health and Medical Data: 3 Short Lunchtime Bites Webinars in May 2017 Workshops with Health Libraries Australia: 10 medical and health research data Things 'train the trainer' workshops. 31 May in Brisbane, 13 June in Melbourne, 14 July in Perth. For health librarians.
- 32. Senior Data Management Specialist [email protected] +61 2 6125 0586 Dr Paul Wong With the exception of logos, third party images or where otherwise indicated, this work is licensed under the Creative Commons 4.0 International Attribution Licence. ANDS is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program. Monash University leads the partnership with the Australian National University and CSIRO.
Editor's Notes
- #3: Note: Data is a very broad church within research. ANDS’ focus is primarily on digital data – not data in the “physical form” e.g. soil or tissue samples. Inclusive in our understanding of digital data, from all disciplines, e.g. quantitative and qualitative data, multi-media data (audio, images, videos), computer models.
- #4: About 40 guides have been developed across a spectrum of data management topics
- #17: 15 key points – with short descriptions, 7 pages long. incorporating project management best practice Shared responsibilities model Continual data curation approach