Eric Jensen and Mark Reed, in the second of two blog posts, explore who benefited from data-intensive research in the UK and Australia.
Many researchers hope that the data that they generate will make a positive difference in the world. As established in our previous blog post, such impact is rarely delivered directly through research data alone.
Instead, active measures are required to augment research data in targeted ways to deliver impact.
Here, we present further findings from our research commissioned by the Australian Research Data Commons (ARDC) aimed at revealing how research data contributes to non-academic impacts.
This research draws on a secondary analysis of existing impact case studies from the UK Research Excellence Framework (REF) and the Australia Research Council (ARC) Engagement and Impact Assessment 2018.
Who benefited from the research data-linked impact?
Professionals (50% UK), government, policy, or policymakers (42% UK; 28% Australia), industry and business (38% UK; 21% Australia), and specific publics (16%) were the most common types of beneficiaries from the research data-linked impacts we analysed.
This finding is indicative of a two-step flow from data to impact that ultimately reaches publics or wider non-academic stakeholders:
- intermediaries such as the government, policymakers, and businesses are typically the primary beneficiaries of research data-based impacts;
however
- they often in turn use what they have gained to develop further insights, services, products, and policies that deliver broader public benefits.
Looking at patterns in this analysis, the following statistically significant associations were identified:
- Reports or other types of static information tended to be used most with government stakeholders, and significantly less with industry and business.
- Analytic software or methods as well as shared technology or software were used more to develop impacts with industry and business, and significantly less with specific publics.
- Professionals as opposed to government stakeholders tended to benefit most from improved institutional processes.
- The general public tended to benefit from other impact instruments, e.g. gaining benefits via policy change.
Various connections were found between predictor variables and certain outcomes such as identified types of impact and beneficiaries, for example:
- The field of research, that is, which type of academic discipline the research data-linked impacts were attributed to, was found to be a moderate predictor of impacts. For instance, practice impacts were significantly more commonly associated with the field of Psychology and Cognitive Sciences than with other research fields.
- On the other hand, whether the university associated with the impact-linked research data was part of the elite Group of Eight (Go8) in Australia overall did not or only weakly influenced impact patterns.
Finally, it is worth noting that the findings from the Australian EI 2018 case studies are broadly similar to the UK REF impact case study findings.
This similarity suggests that there may be structurally parallel patterns internationally in how research data are used to develop non-academic impacts.
Conclusions
The analysis found that research data on their own rarely lead to impact, but instead they require analysis, curation, product development or other interventions to leverage broader non-academic value from the research data.
These interventions help to bridge the gap between research data – which might otherwise go unused for the purpose of developing impact – and the diverse range of potential primary and secondary beneficiaries.
As such, impact from research data may be increased through closer links between government, industry and researchers, as well as capacity building at each of these levels.
Capacity building initiatives can be aimed at potential impact beneficiaries, including supporting them to access useful sources of research data, and either understand and make use of this data or adapt it to serve new purposes.
As such, the way that research data are made available, and the nature of the support available for interpreting and using this data, can affect how feasible it is to use that research data to develop new and creative pathways to impact.
Find out more
- Our open access PLOSONE paper on developing impact from research data
- Training and resources on evaluating research impact: Methods for Change
- Training and resources on research impact: Fast Track Impact
- Learn more about the ARDC
About the authors
Eric A. Jensen is Associate Professor of Sociology at the University of Warwick, Director of Research at the Institute for Methods Innovation and The Brinson Foundation Civic Science Fellow at the Advanced Visualization Lab, National Center for Supercomputing Applications (NCSA), University of Illinois.
Specializing in evidence-based science communication (sciencecomm.science) and research impact evaluation, he has 20+ years of experience in social research and evaluation. Eric’s books include Doing Real Research: A Practical Guide to Social Research (SAGE) and Science Communication: An Introduction (World Scientific).
Mark Reed is Professor of Rural Entrepreneurship and Co-Director of the Thriving Natural Capital Challenge Centre at Scotland’s Rural College (SRUC), and CEO of Fast Track Impact.
He researches environmental governance and research impact, and has >200 publications that have been cited >20,000 times.