The document discusses open data and data sharing, including defining open data, the benefits of open data, overcoming barriers to opening data such as concerns about scooping and sensitive data, best practices for making data open through formats, licensing and description, and the role of research databases and data citation in promoting open data.

1. 23 Research Data
Things
Research Data Coordinator
Katina Toufexis

2. Data Sharing
• Research data may be shared in many ways.
• Getting Started looks at sharing data via access methods: Open, Shared
and Closed Data
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3. Data Sharing
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https://vimeo.com/125783029
Open / Shared / Closed: The world of data

4. Data Sharing
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1. What is 'open data'?
2. Who benefits from open data?
3. Overcoming barriers to opening data
4. Making data open
5. Open data in Research Data Australia

5. Data Sharing
Thing 5
1. What is 'open data'?
2. Who benefits from open data?
3. Overcoming barriers to opening data
4. Making data open
5. Open data in Research Data Australia

6. Thing 5
What is 'open data'?
1. freely available to download in a reusable form. Large or complex data
may be accessible via a service or facility that enables access in-situ or
the compilation of sub-sets
2. licensed with minimal restrictions to reuse
3. well described with provenance and reuse information provided
4. available in convenient, modifiable and open formats
5. managed by the provider on an ongoing basis.
The Open Data Handbook provides an introduction to the legal, social and
technical aspects of open data. It discusses what open data is as well as why
and how to make data open.

7. Thing 5
Open Data Handbook

8. Data Sharing
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1. What is 'open data'?
2. Who benefits from open data?
3. Overcoming barriers to opening data
4. Making data open
5. Open data in Research Data Australia

9. Thing 5
Who benefits from open data?
Everyone! According to the Royal Society, open data supports:
• new research and new types of research
• the application of automated knowledge discovery tools online
• the verification of previous results
• a broader base set of data than any one researcher can hope to collect
• the exploration of topics not envisioned by the initial investigators
• the creation of new data sets, information and knowledge when data from
multiple sources are combined
• the transfer of factual information to promote development and capacity
building in developing countries
• interdisciplinary, inter-sectoral, inter-institutional and international research.

10. Thing 5
Who benefits
from open data?
The many ways
open data benefits
researchers,
research
organisations,
funders, policy
makers and the
broader
community:

11. Data Sharing
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1. What is 'open data'?
2. Who benefits from open data?
3. Overcoming barriers to opening data
4. Making data open
5. Open data in Research Data Australia

12. Thing 5
Overcoming barriers to opening data
Someone might use my data to 'scoop' me

13. Thing 5
Overcoming barriers to opening data
Someone might use my data to 'scoop' me
1. Timing?
You may choose to restrict access to your data until a key paper is published.
You decide the appropriate time for making your data open.

14. Thing 5
Overcoming barriers to opening data:
Someone might use my data to 'scoop' me
2. What is the real risk of ‘scooping’?
Little risk according to:
Nature, Professor Issac Kohone, Harvard Medical School: "[we] need to
convince people that the likelihood of being scooped if they put their data out
there [is] not going to be high ... we need to do away with a culture of sitting on
data until we have mined every useful scientific grain out of it".
In a similar vein, some researchers report that any possible loss of future
potential papers is well offset by the more immediate rewards of data citations
and collaborative opportunities.

15. Thing 5
Overcoming barriers to opening data:
Someone might use my data to 'scoop' me
3. What is the real risk of ‘scooping’?
In fact, many researchers find that opening up their data has greatly benefited
their research.
Report - Professor Tim Gowers, Royal Society Research Professor, University
of Cambridge
• opened up his data to crowd-source an unsolved mathematical problem.
• 27 people made 800 substantive contributions to solve the problem in a
matter of days.
• Professor Gowers commented that this approach to research was "like driving
a car whilst normal research is like pushing it".

16. Thing 5
Overcoming barriers to opening data:
My data are sensitive due to cultural, ethical, ecological or security
considerations
There are circumstances where it may not be appropriate to make data open.
e.g.
• where individuals may be identified;
• threatened species located; or
• information affecting national security revealed.

17. Thing 5
Overcoming barriers to opening data:
My data are sensitive due to cultural, ethical, ecological or security
considerations
However, there may be ways to make sensitive data at least
partially open.
This comprehensive 26 page Publishing and Sharing
Sensitive Data - ANDS Guide (PDF, 0.73 MB) outlines
best practice for the publication and sharing of sensitive
research data in the Australian context. It should be read
in conjunction with the ANDS Introduction to Sensitive
Data.

18. Thing 5
Overcoming barriers to opening data:
My data are sensitive due to cultural, ethical, ecological or security
considerations
http://www.ands.org.au/__data/assets/pdf_file/0010/385309/sensitive-
decision-tree.pdf
ANDS Publishing and Sharing Sensitive Data DECISION TREE

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20. Thing 5
Overcoming barriers to opening data:
I won't get any recognition or reward for making my data open
Tools such as Thomson Reuters Data Citation Index, enable citation metrics to
be captured for data

21. Thing 5
Overcoming barriers to opening data:
There are contractual or commercial interests associated with my data
• research data may underpin a commercialisation opportunity such as a
patent.
• Or it may be that contractually, IP arising from a project is owned by a third
party.
• In others cases though, data is not shared because of the uncertainty arising
from data not being explicitly addressed in contracts and project plans.

22. Data Sharing
Thing 5
1. What is 'open data'?
2. Who benefits from open data?
3. Overcoming barriers to opening data
4. Making data open
5. Open data in Research Data Australia

23. Thing 5
Making Data Open
Open data is Which ideally means ... So preferably not ...
Freely available
to download
a) There is no cost to access the data;
b) Access is via an internet accessible
download;
c) Data is in a form that can be readily
downloaded. Large or complex data is located
close to high performance computing or
specialised services that enable access to the
data in situ or the compilation of sub-sets.
a) Costed at more than
reproduction cost;
b) Burned to a DVD and posted
via 'snail mail';
c) Only available in huge
packages that are difficult to
reuse and/or take days to
download.
Licensed An open license such as CC-BY is applied.
A restrictive license, or worse, no
license at all. If no license is
applied, no reuse is permitted.
Well described
Standards based metadata is used with details
of data elements and inclusion of data
dictionaries. Describe the purpose of the
collection, the characteristics of the sample and
the method of data collection.
Metadata descriptions that are
very brief or will not be widely
understood. Avoid jargon and
abbreviations and don't assume
prior knowledge of the data or
subject domain.
Provided in an
open format
The data is in a convenient, modifiable and
open format that can be readily retrieved,
downloaded, indexed and searched. Where
possible, formats should be machine-readable
and non-proprietary formats are preferred. For
example, prefer netCDF over .xls.
Obscure formats or formats that
require proprietary software to
open and reuse.
Well managed
The data is managed on an ongoing basis with
a point of contact designated to assist with data
use.
Data that is loaded on to a
server and forgotten.

24. Data Sharing
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1. What is 'open data'?
2. Who benefits from open data?
3. Overcoming barriers to opening data
4. Making data open
5. Open data in Research Data Australia

25. Data Sharing
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Open data in
Research Data
Australia
1. New Interface
highlights the
openness of
data
2. Licenses can
be applied

26. Data Sharing
Wiley Survey
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http://www.acscinf.org/PDF/Giffi-%20Researcher%20Data%20Insights%20--%20Infographic%20FINAL%20REVISED.pdf

27. Long-lived data: curation & preservation
https://youtu.be/qEmme
FFafUs
US Library of Congress
(LoC)
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28. Long-lived data: curation & preservation
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29. Long-lived data: curation & preservation
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What key advice would you give someone about preserving
their born digital objects e.g. the family historian, a researcher,
yourself? ….Hint: look for ideas on the Library of Congress
Digital Preservation website.

30. Long-lived data: curation & preservation
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31. Long-lived data: curation & preservation
Video - http://www.clir.org/initiatives-partnerships/data-curation
Sayeed Choudhury, Associate Dean for Research Data Management at Johns
Hopkins University (long video… to summarise)
 Talks about the Stack Model for Data Mgt
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Storage
•Disk, tape, cloud etc.
Archiving
•Identifiers for sharing and
references
Preservation
•Policy, metadata, long-term
reuse
Curation
•Adding value to data for
reuse

32. Data citation for access & attribution
• Data citation continues the tradition of acknowledging other people’s work
and ideas.
• Along with books, journals and other scholarly works, it is now possible to
formally cite research datasets and even the software that was used to
create or analyse the data.
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33. Data citation for access & attribution
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34. Data citation for access & attribution
https://resear
chdata.ands.
org.au/mont
hly-drought-
australia-
drought-
index/61872
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35. Data citation for access & attribution
http://ands.org.au
/working-with-
data/citation-and-
identifiers/data-
citation
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36. Thing 7
Data citation for access & attribution
Force11 Joint Declaration of Data Citation Principles
• a set of principles for citing data.
• based on the premise that data citation, like the citation of other evidence
and sources, is good research practice and is part of the scholarly
ecosystem supporting data reuse.
Since they were published 2 years ago, the Principles have been endorsed by
numerous individuals and more than 100 data centres, publishers and societies.

37. Thing 7
Data citation for access & attribution

38. Thing 7
Data citation for access & attribution
Force11 is endorsed by…
https://www.force11.org/datacitation/endorsements

39. Thing 7
Data citation for access & attribution
Given such support and clear direction,
why do you think data citation has not been uniformly adopted, so far, across all
disciplines?

40. Citation Metrics for Data
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What are Digital Object Identifiers (DOIs)
and how do they support data citation and
metrics for data and related research
objects?

41. Citation Metrics for Data
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DOIs are:
• unique identifiers
• provide persistent access to published articles,
datasets, software versions and a range of other
research inputs and outputs.
• over 120million DOIs in use,
• last year DOIs were “resolved” (clicked on) over
5 billion times!
• typical DOI looks like this:
http://doi.org/10.4225/08/50F62E0D359D5

42. Citation Metrics for Data
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Google “The compendium of crop
Proteins with Annotated Locations
(cropPAL) version 1 ”

43. Data citation for access & attribution
http://ands.org.au
/working-with-
data/citation-and-
identifiers/data-
citation
Remember in Thing 7…

44. Citation Metrics for Data
Here’s a controversial question to discuss:
Should DOIs be routinely applied to all research outputs?
Remember that DOIs carry an expectation of persistence
(maintenance costs etc.) but can provide be used to collect
metrics as well as link articles and data (evidence of impact.)
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45. Thing 8
Citation Metrics for Data
• Alternative metrics or altmetrics count the number of views, number of
downloads, social media "likes" and recommendations associated with a
dataset.
• Because of their immediacy, altmetrics can be an early indicator of the
impact or reach of a dataset; long before formal citation metrics can be
assessed.

46. Thing 8
Citation Metrics for Data
http://classic.science
mag.org/articleusage?
gca=sci%3B346/6210
/763
Start by looking at the
almetrics for this
Phylogenomics
article published in
Science.

47. Thing 8
Citation Metrics for Data

48. Thing 8
Citation Metrics for Data
Look also at the
associated data in
Dryad noting that the
data has been
assigned a DOI.

49. Thing 8
Citation Metrics for Data
By way of comparison, as of early April 2016:
• the same dataset had been cited once in Thomson Reuters Data Citation Index
• the article had been cited 143 times in Web of Science
Share your thoughts
Do you think altmetrics for data have value in academic settings? Why?

50. Contacts
Contact UWA 23 Things Coordinators:
Caroline Clark
caroline.clark@uwa.edu.au
Nola Steiner
nola.steiner@uwa.edu.au
Katina Toufexis
katina.toufexis@uwa.edu.au