The Australian Research Data Commons (ARDC) enhances the value of Australia's research data assets through resources and workshops. It emphasizes the importance of effective data management practices, including the FAIR principles for data stewardship, to ensure data is findable, accessible, interoperable, and reusable. The document outlines guidelines for managing research data, promotes open data practices, and stresses the need for ethical considerations when sharing data.

1. Paul Wong
Research Integrity Advisor Data
Management Workshop
UTS, 21 June 2018

2. The Australian Research Data Commons (ARDC) makes
Australia’s research data assets more valuable for
researchers, research institutions and the nation.
Research Data Australia
Cite My Data / DOIs minting
In 2016/7, 163 workshops, forums, and
webinars etc., over 8,000 participants
Developed online resources, guides,
videos etc.
Co-funded 304 data projects, $62Min total
2018 focus is Data Enhanced Virtual Labs
(STEM& HASS)

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

5. Research data: as input & output
Research data may include:
ü Laboratory and field notes
ü Raw experimental data
ü Analysed data
ü Simulations and software
ü Databases
ü Clinical data, including clinical
records
ü Questionnaires/surveys
ü Images and photographs
ü Audio-visual materials
Moynihan's field notes,
Panama, 1958 – CC BY
https://flic.kr/p/dmXHkJ
Screen capture of “Com puter sim ulation of M arch 22,
2014 landslide event near O so, W ashington, by David
L. G eorge and Richard M . Iverson, USG S”
http://youtu.be/2NzHCO hKr7g CC BY

6. Creative arts research data
Research data in the creative arts may include:
ü Audio-visual recordings of a creative work
ü Visual diaries
ü Journals
ü Drawings
ü Photographs
ü Manuscripts
ü Musical annotations
ü 3D models

7. 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
ARDC’s primary focus is digital data

8. Why Bother?
Why managing (digital) research data?
In fact, why bother managing anything?
• Prevent bad things from happening.
• Enable good things to happen.

9. Data and Research Integrity
Nature 533, 452–454 (26 May 2016) doi:10.1038/533452a. Reprint with permission © 2016 Macmillan

10. 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.”

11. 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
Data contribution to Research Impact in the U.K.
http://www.ands.org.au/working-with-data/articulating-
the-value-of-open-data/data-engagement-and-impact

12. 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

13. 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”

14. http://www.ands.org.au/__data/assets/pdf_file/0009/394056/research-data-m anagem ent-in-practice.pdf

15. Continual data curation across domains

16. 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.

17. Light Touch Heavy Duty
EML
ISO 19115
Darwin Core
Data citation
Ecological
Geographic
Biological
Metadata
Structured
Detailed
Machine readable
Structured
Minimal
Human readable

18. 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

19. 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

20. 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

21. Data Management Plan Planning
• 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

22. Storage requirements may vary across domains

23. 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 role
Post Research
mediated
Personal Data: obtain consent to share from participants at the start!

24. https://www.ada.edu.au/ada/home

25. 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://com m ons.wikim edia.org/wiki/File% 3AFoot_and_M outh_Disease_M ap_-_geograph.org.uk_-_564718.jpg
Colin Sm ith [CC BY-SA 2.0] (http://creativecom m ons.org/licenses/by-sa/2.0)], via W ikim edia Com m ons from W ikim edia Com m ons)

26. 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 HealthUK, 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 observedaroundthe 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 completionof the research.
• Had toget consent retrospectively and neededexpert advice fromcopyright specialists

27. http://www.ands.org.au/__data/assets/pdf_file/0009/394056/research-data-m anagem ent-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.

28. Senior Data Management Specialist
Paul.Wong@ands.org.au
+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.
ARDC is supported by the Australian Government through the
National Collaborative Research Infrastructure Strategy Program.