Towards Open Research

practices, experiences, barriers and opportunities

CPD25: Open Access and Repositories26 April 2017

Veerle Van den Eynden Gareth Knight(Presenter)

Anca Vlad

UK Data ServiceUniversity of Essex

London School of Hygiene & Tropical Medicine

UK Data ServiceUniversity of Essex

Open Research study

• Researchers funded by Wellcome Trust and ESRC: biomedical, clinical, population health, humanities, social sciences

Current attitudes and practices related to sharing of:

• Publications

• Data

• Code

Barriers that inhibit or prevent researchers from sharing

Identification of action that funders can take to encourage good practice and mitigate issues

• Survey (N=583 + 259), focus groups (N=22)

Van den Eynden, Veerle et al. (2016) Towards Open Research: Practices, experiences, barriers and Opportunities. Wellcome Trust. https://doi.org/10.6084/m9.figshare.4055448

Article publishing

• Respondents published average of 18-peer reviewed papers during past 5 years

– 30% published all papers as OA

• Factors that affect ability to publish OA:

– Journal lacks OA option (31%)

– Lack of funds to cover APCs (30%)

– Papers uploaded to social network (8%)

– Lead author decided against OA (4%)

• 50% of respondents use WT funds for APCs:

– Humanities & social scientists less likely than Biomedical & clinical scientists

– Early-career less likely than more established researchers

Open access cookie (CC BY-NC-SA 2.0)https://www.flickr.com/photos/biblioteekje/6325328112/

Data sharing

95% of respondents generate research data, of which 52% made it available in last 5 years

Data sharing methods

414 respondents share data:

• Full dataset (51%)

• Data subset linked to paper (38%)

• Other subset of data (37%)

Via:

• Community repositories (42%)

• Institutional repositories (37%)

• Project/private repositories (15%)

• General purpose repositories (13%)

• Journal supplementary (10%)

Reasons to share data

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

My funder requires me to share my data(N=273)

Journal expects data underpinning findings to be accessible(N=273)

My research community expects data sharing(N=274)

It is good research practice to share research data(N=277)

It enables collaboration and contribution by other researchers(N=274)

It has public health benefits, e.g. disease outbreaks(N=265)

Ability to respond rapidly to public health emergencies(N=263)

Ethical obligation towards research participants to maximize benefits for society(N=266)

Contributes to academic credentials(N=273)

Enables validation and /or replication of my research(N=275)

Improved visibility for my research(N=273)

I can get credit and more citations by sharing data(N=267)

Not at all important Slightly important Moderately important Very important Extremely important

Source: Wellcome survey results

Barriers to data sharing

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

I may lose publication opportunities if I share data(N=517)

Others may misuse or misinterpret my data(N=519)

I have insufficient skills to prepare the data(N=505)

It requires time/effort to prepare my data for deposit(N=520)

I do not have sufficient funding to prepare data for sharing(N=509)

I do not have permission (consent) from my research participants to share data(N=510)

Data contain confidential / sensitive information and cannot be de-identified(N=504)

My data are commercially sensitive or has commercial value(N=501)

There are third party rights in my data(N=499)

No suitable repository exists for my data(N=502)

Country-specific regulations do not allow sharing(N=486)

Not at all important Slightly important Moderately important Very important Extremely important

Source: Wellcome survey results

Motivations for more data sharing

Source: Wellcome survey results

Significant differences in motivationM

OR

E IM

PO

RTA

NT

LESS

IMP

OR

TAN

T

Extra funding to cover costs

established researchers

~

cell, development and physical

science, genetic and molecular

science, neuroscience and

mental health, population health

infection and immunobiology

Enhanced academic

reputation

early career researchers

~

researchers not sharing data now

Co-authorship on reuse papers

early career researchers

clinical, population health,

social science researchers

cell, devel and physical science,

neuroscience and mental health

biomedical and humanities

researchers, genetic and molecular science,

infection and immunobiology

Case study that showcase data

LMIC researchers

~

humanities, Infection and

immuno-biology, population health

cell, development and physical science,

genetic and molecular science, neuroscience

and mental health

Data deposit leads to data

paper publication

early career researchers; LMIC

researchers

~

cell, development and physical

science, infection and immuno-

biology, neuroscience and

mental health

genetic and molecular science, humanities and social sciences

Considered favourably in funding and promotion decisions

UK-based researchers

~

cell, development and physical

science, genetic and molecular science,

neuroscience and mental

health

Population health

Ability to limit data access to

specific purposes or individuals

LMIC researchers

~

clinical, population health and

social science researchers

biomedical researchers

Assistance from institution or

funder to prepare data

clinical, population health and

social science researchers

biomedical and humanities researchers

Code sharing

40% of respondents generate code:• Researchers performing surveys, observations, experiments,

secondary analysis & simulations more likely to produce code

43% of these shared code in last 5 years:• Researchers performing simulations and secondary analysis

more likely to share code

• Researchers applying qualitative methods less likely to share code

37% reuse existing code:• Obtain from colleagues, collaborators & community repositories

• Influencing factors in code reuse: good documentation, reputable source, and open availability

Shared via institutional, community & journal services

Reasons to share code

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

My funder requires me to share my code(N=97)

Journal expects code to be accessible(N=97)

My research community expects code sharing(N=97)

It is good research practice to share code(N=101)

To enable collaboration and contribution (N=98)

Contributes to my academic credentials(N=95)

Enables validation of my research(N=97)

Enables replication of my research(N=96)

Improved visibility for my research(N=95)

I can get credit and more citations by sharing code(N=91)

Not at all important Slightly important Moderately important Very important Extremely important

Source: Wellcome survey results

Code sharing benefits

0 5 10 15 20 25 30 35 40

Career benefits

More publications

Higher citation rate

New collaborations

More funding opportunities

Financial benefit

New patents

Improvements to public health

Use in health emergencies

None

Other

Source: Wellcome survey results

Code sharing barriers

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Desire to patent (N=210)

Protecting intellectual property (N=213)

Software and systems dependencies (N=213)

I may lose publication opportunities if I share code (N=210)

Others may misuse or misinterpret my code (N=211)

Insufficient skills to prepare the code for public use (N=213)

It requires time/effort to prepare my code for deposit (N=217)

Insufficient funding to prepare code for public use (N=211)

My code has commercial value (N=207)

There are third party rights in my code (N=206)

No suitable repository exists for my code (N=197)

Not at all important Slightly important Moderately important Very important Extremely important

Source: Wellcome survey results

Motivations for more code sharing

0 10 20 30 40 50 60

Financial incentive from my institution

Extra funding to cover the costs

Enhanced academic reputation

Code access and metrics

Knowing how others use my code

Co-authorship on papers resulting from reuse

Case study that showcases my code

It is looked on more favourably in funding and promotion decisions

Evidence of code citation

Assistance from institution/funder staff to prepare code

Nothing motivates me

Source: Wellcome survey results

Recommendations

Funding:

• Dedicated funding streams for data/code preparation

• Guidelines for describing code development & sharing in funding bid (Software Management Plan?)

• Demand for investment in support staff to help with data/code preparation

Rewards:

• Recognise data & code sharing in career progress evaluation

• Citations and co-authorship for new publications based upon shared data/code

• Build evidence of good practice – case studies.

Infrastructure:

• Utilise existing infrastructure where possible, e.g. GitHub, SourceForge, CRAN for R code, etc.

• Enhance functionality - granular access controls, big data, enhanced citation and reuse metrics

Support:

• Enhance networking / support opportunities for data/code creators and re-users

• Develop training – software carpentry, Software Sustainability Institute

Further Developments

https://wellcome.figshare.com/ https://wellcomeopenresearch.org/

Thanks to:All researchers who contributed to the surveys and focus groups

Wellcome Trust:David CarrRobert Kiley

Expert advisors:Barry Radler (University of Wisconsin),Carol Tenopir (University of Tennessee), David Leon, Jimmy Whitworth (LSHTM) Frank Manista (Jisc)Louise Corti (UK Data Service)