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Dr	Paul	Wong
Research	Integrity	Advisor	Data	
Management	Workshop
Senior	Data	Management	Specialist
16	June	2017	Adelaide
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.
• 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
• 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
https://projects.ands.org.au/policy.php
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 “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
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
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
Why	Bother?
Why	managing	(digital)	research	data?
In	fact,	why	bother	managing	anything?
• Prevent	bad	things	from	happening.
• Enable	good	things	to	happen.
Data	and	Research	Integrity
Nature 533, 452–454 (26 May 2016) doi:10.1038/533452a. Reprint with permission © 2016 Macmillan
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.”
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
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
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”
http://www.ands.org.au/__data/assets/pdf_file/0009/394056/research-data-management-in-practice.pdf
Continual data curation across domains
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.
Light	Touch Heavy	Duty
Ecological
Geographic
Biological
Metadata
Structured
Detailed
Machine readable
Structured
Minimal
Human readable
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
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
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
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
Storage requirements may vary across domains
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
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)
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
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.
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.
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)
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.
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.
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.

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