Covid Impacts ECRs Data Sharing

Research in the time of Covid:
Surveying impacts on Early
Career Researchers
Dr. Rebecca Grant, Springer Nature
April 2021
Illustration
inspired
by
the
work
of
Chien
Shiung
Wu

1
Research in the time of Covid: EARMA 2021
1
Surveying researchers during the global pandemic:
the State of Open Data

2
90% of researchers have been impacted by Covid-19
32% report that they were very or extremely impacted,
compared to 26% of those in the professional sphere

3
• What have the impacts been on researchers in 2020?
• How do ECRs compare to those at other career
stages?
• What is the connection between pandemic-related
impacts and Open Data sharing and reuse?
• How can we support shifting priorities?
Covid, Open data and ECRs

4
• The report is a collaboration
between Springer Nature, Digital
Science and figshare
• 5 years of longitudinal global
survey data (2016-2020)
• 2020 survey was conducted
between March and July 2020
and received nearly 5000
responses.
The State of Open Data reports

5
Understanding researchers’ needs & challenges
Published April 2019, our 5 essential factors report brings
together findings from surveys with more than 11,000
researchers worldwide.
Published April 2019, our 5 essential factors report
brings together findings from surveys with more than
11,000 researchers worldwide.
https://figshare.com/articles/Five_Essential_Factors_for_Data_Sharing/7807949

6
4945 responses:
• Africa (7%)
• Asia (including Middle East) (26%)
• Australasia (3%)
• Europe (35%)
• North America (including Central America
and the Caribbean) (20%)
• South America (8%)
Special topics this year:
• COVID19 and changing habits: Use
and reuse of data
• Credit and misuse of data
• Data management
The State of Open Data 2020
Report & anonymised data are available:
Report: https://doi.org/10.6084/m9.figshare.13227875
Anonymised dataset (CC licence):
https://doi.org/10.6084/m9.figshare.13274744
22% early career researchers
(ECRs) globally, (n=965)
• Undergrads
• Masters students
• Ph.D. students
• PostDocs
• Research assistants

7
• A third (32%) of academic researchers reported that their research had been
‘extremely’ or ‘very’ impacted by the outbreak of COVID-19
• The disciplines affected most by COVID-19 were those working in Chemistry (47%),
Biology (39%), Medicine (36%) and Materials Science (36%). The lowest level of impact
was reported in Humanities and Social Sciences (20%)
• 43% of those surveyed have already or are likely to repurpose their grant to some
extent for COVID-19 research.
• Lockdown is seen by half of respondents as ‘extremely’ or ‘somewhat’ likely to result in
re-use of open data provided by other labs, and 65% expect to reuse their own data
• More than a third of researchers say they expect to see more collaboration as a result of
COVID-19; for those in countries like Brazil and India where the impact of COVID-19 on
research appears significant, around half expect collaboration to increase as a result.
Key findings:

8
COVID and ECRs
‘With the outbreak of COVID-19, to what extent has your
research been impacted?’
24% can’t
do MOST
of their
work
9% can’t
do ANY of
their
work

9
Higher impact than other career stages: 33% Extremely or very
impacted
9%
24%
32%
27%
8%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Extremely impacted (can't do any of my work)
Very impacted (can't do most of my work)
Impacted (can't do some of my work)
Slightly impacted (can do most of my work as usual)
Not impacted (can do all of my work as usual)
Senior researcher Mid-career researcher Early-career researcher
‘With the outbreak of COVID-19, to what extent has your research been impacted?’

10
10
Why is data reuse significant?

11
The inability of many researchers to gain access to their labs or carry out new
research has fuelled a planned increase in the reuse of their own and others’
data.
Why data reuse?
50% will
reuse
others’
data
65% will
reuse
their own
data
All career levels

12
Data reuse before the pandemic
54%
61%
59%
46% 46%
44%
29%
25%
27%
0%
10%
20%
30%
40%
50%
60%
70%
Early-career researcher Mid-career researcher Senior researcher
Your own data
Openly accessible data shared by
other researchers
Neither of the above
‘Prior to the COVID-19 outbreak, had you ever reused [data] as part of your
research?’

13
Data reuse during the pandemic
36%
31%
8%
6%
8%
11%
Your data - while in lockdown
Extremely likely
Somewhat likely
Neither likely nor
unlikely
Somewhat unlikely
Extremely unlikely
Not applicable
24%
32%
14%
8%
11%
12%
Others' data - while in lockdown
‘Since the outbreak of COVID-19, how likely are you to reuse either your own data or
that of others as part of your research?’
(ECRs only, n=965)
~10-15%
increase
in reuse
intention

14
Data reuse in the future
38%
31%
11%
6%
6%
8%
Your data - over the next 12-18 months
Extremely likely
Somewhat likely
Neither likely nor
unlikely
Somewhat unlikely
Extremely unlikely
Not applicable
22%
34%
16%
8%
10%
11%
Others' data - over the next 12-18
months
‘Since the outbreak of COVID-19, how likely are you to reuse either your own data or
that of others as part of your research?’
(ECRs only, n=965)

15
Data sharing is essential for data reuse
Self-storage/sharing on request
Sharing as supplementary files
Sharing in a data repository
More common
Less common

16
Concerns around data sharing
35%
33%
31%
30%
29%
22%
22%
18%
18%
17%
15%
14%
11%
10%
9%
9%
2%
1%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Concerns about misuse of data
Unsure about copyright licensing
Not receiving appropriate credit or acknowledgment
Contain sensitive information or require permissions
Unsure I have permission to share
Organising data in a presentable and usable way
Costs of sharing data
I'm not sure I've exhausted all the potential findings yet
Lack of time to deposit data
Not know what repository to use
Another lab may make a different interpretation
Data are too large to share
Data are too small or unimportant
I have no problemns/concerns about sharing data
Others may find errors in my data
Others may not be able to repeat my findings
I have no desire to share my data
Other
‘What problems/concerns, if any, do you have with sharing datasets?’

17
Emergent concerns during the pandemic
Scooping?
Academic
misconduct?
All career levels
Published, citable datasets should be recognised as an equal
research output to the paper.

18
Data sharing: a matter of policy

19
ECRs are in favour of data sharing and open data
Significantly more supportive of funder mandates
62%
57%
52%
16%
20% 22%
22% 24%
26%
0%
10%
20%
30%
40%
50%
60%
70%
Yes
No
I don't know
‘Should funders make the sharing of research data part of
their requirements for awarding grants?’

20
What would motivate ECRs to share?
‘What circumstances would motivate you to share your data?’
69%
64%
63% ↑
60%
58% ↑
55% ↓
50%
47% ↑
47%
36%
36% ↑
35% ↑
29%
19%
2%
1%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Full data citation
Increased impact and visibility of my research
Journal/Publisher requirement
Public benefit
Greater transparency and reuse
Co-authorship on papers
Funder requirement
Consideration in job reviews and funding applications
Institution/Organisation requirement
Direct request from other researcher
Financial reward
Freedom of information request
It was made simple and easy to do
I was a field/industry expectation
Other
I would never share my data

21
What would motivate ECRs to share?
Credit
(citation)
Strong
policies
(funder &
publisher)
ECRs are nearly as motivated by strong policies (63%) as by credit in
the form of full data citations (69%)

22
ECRs are in favour of data sharing and open data
Significantly more supportive of funder mandates
57%
54%
52%
18%
22% 24%
26% 24% 25%
0%
10%
20%
30%
40%
50%
60%
Yes No I don't know
‘Should funders withhold funding from (or penalise in other ways)
researchers who do not share their data if the funder has mandated
that they do so at the grant application stage?’

23
What does it mean to manage and share data?
Repositories
Policy
compliance
Sharing and
licensing for
reuse
Storage
Security
Data
management
planning

24
ECRs see gaps in their data management skills
3%
44%
48%
48%
56%
61%
0% 10% 20% 30% 40% 50% 60% 70%
None of the above
Defining the data to be produced and how it's
acquired
Costing and budget planning
Metadata descriptions
Understanding and defining policies for access,
sharing and re-use
Long-term storage and data management
strategies
‘In which, if any, aspects of data management planning do you feel you
would benefit from further skills training?’
(ECRs only, n=965)

25
ECRs need more support to manage & share data
2%
7%
34%
37%
43%
44%
47%
55%
0% 10% 20% 30% 40% 50% 60%
Other
None of the above
Curation of data
Finding the time to manage my data
Data management plans
Finding appropriate repositories
Data management policies
Copyright/licensing of data
‘What areas, if any, do you feel you need help with in regard to making
your research data openly available?’
(ECRs only, n=965)

26
• Increased willingness to reuse data
• Motivated by strong policies
• Key areas where support is needed
Covid: impacts and opportunities

27
Opportunities: additional support for ECRs post-Covid
Clarity of what’s expected:
How to fit with institution,
funder and publisher
expectations
Impact and visibility: Building
their reputation
Support career development:
Essential career skills
Creating a generation of better
researchers: reproducibility,
research integrity and open
science/research practices

28
1. Journal policies and data citation
Journal policies promote citation of datasets in reference lists
Publisher actions are needed to ensure these are marked up/machine-
discoverable
2. Improving data linking to support reuse
Publishers are collaborating to implement better ways to measure and
track reuse of data through citations
3. Data publishing options in peer-reviewed journals
Data journals, such as Scientific Data, provide a means to gain
publication credit specifically for publishing and describing datasets
Collaborations and initiatives to promote credit and
recognition for data sharing

29
Training and education required to support
best practice
Choosing
repositories
Copyright
and
licensing
Data
manageme
nt planning
Sensitive
data
sharing
Prevent
misuse
Policy
compliance

30

31
Recommended repositories list for all Springer Nature
journals

32
Recommended repositories list for all Springer Nature
journals

33
• 90% of researchers impacted by Covid
• ECRs impacted more than other career stages
• This has led to an increased interest in data reuse -
but skills/support may be lacking
• Policies, incentives and training can help to capitalise
on current momentum
Covid, Open data and ECRs

34
34
The story behind the image
John Maynard Keynes (1883–1946)
John Maynard Keynes was a British economist who
revolutionised the theory and practice of macroeconomics,
reformed economics and had a profound influence on
economic policy. This illustration represents the Keynesian
model which shows that in a monetary economy it is
possible to have periods of high unemployment unless
governments use active monetary and fiscal policy to
stimulate aggregate demand.
Thank you
Dr. Rebecca Grant, Research Data Manager
Rebecca.Grant@springernature.com
https://researchdata.springernature.com/
• State of Open Data 2020:
https://doi.org/10.6084/m9.figshare.13227875
• Dataset: https://doi.org/10.6084/m9.figshare.13274744
Image credits: Louis Reed via Unsplash; and Flaticon.com

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