The road to success: drawing parallels between 'road' and 'research data' infrastructures to foster understanding between service providers, funders and policymakers

Introduction

Data-intensive research depends on data and data services, such as databases, software and tools, and standards. These are often made available to end-users through research infrastructure. Such a research infrastructure for biological data and bioinformatics service in Europe is ELIXIR.¹

As is common for many types of infrastructure (especially those that are free at the point of use), the existence of research infrastructure, like the services provided by ELIXIR, is often taken for granted by their users. Their importance is only noticed when they are (temporarily) unavailable, or worse, could disappear due to discontinued funding.^2,3 In the Kano model, infrastructure services are must-be qualities: their proper functioning does not make the users happy, but service disruptions are strong dissatisfiers.

As research infrastructures and their services are typically funded through the public purse, it is essential that policy makers, research funders, experts reviewing funding proposals, and possibly even end-users are equipped with a good understanding of the daily tasks of service providers. We have noticed that this is not often the case, and this becomes an issue when this lack of understanding affects the funding of research infrastructures. To foster better understanding, this policy brief provides a comparison table of features of data infrastructure and their relatable counterparts in road infrastructure. We believe that using this approach can help, first because the change in mind frame makes it possible to see consequences of certain choices more clearly, especially those linked to funding of research infrastructures. Second, many people, even those working in research, are much more accustomed to road infrastructure setup and road infrastructure disruptions than to research infrastructure setup and research infrastructure disruptions; this increased familiarity increases the chances that consequences of policy decisions are foreseen.

For the actual feature comparison, see Table 1.

Policy outcomes and implications

The comparison between research data infrastructure and road infrastructure has many hooks to support productive discussions, and decisions, on research infrastructure funding and sustainability governance. Given that we, the co-authors, all work in research infrastructures, there is an inherent bias in the approach presented, just like when Sutherland et al.⁴ published their “20 things politicians need to know about science”. Yet, we also do not intend to be counterproductive: policymaking is complex and multifaceted, as astutely explained in “20 things scientists need to know about policy”. The comparison table is simply our contribution to fostering longer-term sustainability of infrastructures that already exist, that are widely used across the world, and that have typically received significant public financing over the years.

Furthermore, the comparison table is likely to support efforts of both research infrastructure operators and policymakers in more accurately conveying to taxpayers the public value of research infrastructures, in addition to their role as enablers of scientific discovery and applications of societal benefit. The word ‘enablers’ is perhaps the most important message to convey: just like a road enables travel (and a research infrastructure enables research), it is questionable whether it is right to ask the road construction/maintenance company (and the research infrastructure operator) whether the road (and the research infrastructure) bring(s) value to society. Economists and evaluation specialists are very well placed and qualified (and likely unbiased) to answer complex questions around the public value of financing roads and research infrastructures.^5,6

Actionable recommendations

Recommendation 1: When formulating opinions and decisions on research data infrastructure funding and sustainability governance, compare them with that of road infrastructure. The change of frame may bring new insights.

Recommendation 2: Consider informing policies and funding decisions relating to existing and future research infrastructure with support from economists and specialist evaluators.

Conclusion

We welcome any additional rows for the comparison as well as discussion on improving the existing table in the original Google Document. We have found it difficult to broaden the set of comparisons to also include a sustainable travel angle (e.g. examples covering public transport versus private car travel). Considering the climate emergency, this would be a useful and still relatable expansion of the approach.