Understanding organisational, sector-specific, disciplinary and individual factors influencing research data sharing

Claire Mason1, Paul J. Box2, Shanae Burns3

1Data61, CSIRO, Brisbane, Australia, Claire.Mason@data61.csiro.au

2Land and Water, CSIRO, Sydney, Australia, Paul.J.Box@csiro.au

3Data61, CSIRO, Brisbane, Australia, Shanae.Burns@data61.csiro.au



CSIRO’s data governance initiative aims to improve the discoverability, management, accessibility and re-use of research data. One of the first activities carried out under the initiative was an organisation-wide survey whose purpose was to (a) provide a baseline view of data attitudes and practices and (b) reveal how organisational, sector, disciplinary and individual factors were shaping data sharing practices, responses. We report on the findings of the survey and explain how they can be used to inform CSIRO’s institutional and technical responses to promote data sharing and open data outcomes.


The survey was sent to CSIRO staff and affiliates who worked in research units and roles where they were likely to be dealing with research data. Of the 5,704 individuals who received the invitation to participate in the survey, 806 agreed to participate in the survey, representing a 22% response rate for staff and a 1% response rate for affiliates. Apart from the low representation of affiliates in the sample, the survey achieved input from across the range of age-groups, roles, tenure and education levels. Use of data management plans and channels to share research data amongst these respondents was relatively high – 87% of respondents reported sharing or depositing data through one or more channels over the past five years. However, although the response rate was high for a survey of this kind, we did not achieve input from the majority of CSIRO research staff, so these figures may not be representative of data practices organization-wide.


Organisational factors that were assessed in the survey included organizational data culture, peer support for data sharing and organisational support (funding, processes, tools and training) for data sharing. The organisational culture was open, indicating that most respondents believed that data should be made publically available when possible, although respondents also agreed that data was viewed as a source of competitive advantage (which is shared when there is a benefit to the organisation, rather than simply to benefit others). Peer support for data sharing was perceived to be high and the great majority of respondents reported a desire for organisational processes and systems to support data management and sharing, both during and beyond the life of the project.

The survey also revealed that the industry sector or domain area that researchers work in has an impact on their data attitudes and practices. Furthermore, these external influences appear to do more to inhibit than to foster data sharing. Only 39% of survey respondents reported that their funders “encourage” or “mandate” data sharing, whereas most researchers (especially those working with industry rather than government) reported that contractual arrangements, privacy concerns and ownership and licensing arrangements were important inhibitors of their ability to share data.

There was significant variability in the extent to which scientists from different research disciplines experienced support or barriers to data sharing. The conditions for data sharing appeared to be most conducive for environmental scientists (since they were most likely to report that their journal publishers encouraged them to publish their data and that their peers supported data sharing) and least conducive for researchers who worked in the field of studies in human society.

Finally, individual attitudes towards data sharing were generally positive. On average, the career benefits associated with data sharing were seen to outweigh the risks and respondents said that they would be willing to share their data to help another researcher. However, they also believed that they did not always have control over the decision about whether to share their data or not.

To understand how these organisational, sector-specific, disciplinary and individual factors influence data sharing, we asked survey respondents whether they would be likely to share their data externally (beyond the project team and client) over the next twelve months. An ordinary least squares regression model was used to test the relationship between researchers’ perceptions of organizational, sector-specific, disciplinary and individual factors and their views on the likelihood of sharing data externally.

The analysis revealed that social factors had the strongest relationship with external data sharing. The regression model revealed that open data culture, peer support for data sharing, type of science, social influence and willingness to share data all explained significant variance in external data sharing. The overall fit of the model (R2adj = .41, p < .001) was significant and indicates that the significant predictor variables explained 41% of the variance in external data sharing behavior.


These findings should be interpreted with caution because common method variance effects and non-independence in the data may have inflated these relationships. There are also some indications that the strength of these relationships varies, depending on which area of the organization respondents work in, which means that tailored strategies and a federated approach to data governance will be needed.  Nevertheless, the survey provides important insight into data attitudes and practices in CSIRO. First, it reveals that staff understand the value of data re-use but that they are also aware of important factors (e.g., ethics, privacy concerns, contractual arrangements) which constrain data sharing. Staff in some research units and industry sectors (e.g., researchers working for government rather than industry) have more freedom to operate than others when it comes to data sharing.  Finally, the results of our modelling suggest that organisational culture and norms (both within the organisation and within research disciplines) represent important levers for influencing organisational data practices.


Senior social researcher in the CSIRO’s Data61, Claire’s research focuses on understanding the opportunities and challenges associated with our increased reliance on digital technology across a range of contexts – in our homes and businesses, in our jobs, in vocational education and training, in regions and in later life. She also explores how social, organisational and institutional factors influence data practices and thus our opportunities for data driven innovation.

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