This preliminary analysis examines the potential for implementing FAIR data in Denmark by estimating the benefits and costs of introducing FAIR research data in Denmark.
The four principles that make up FAIR include the following: Findable: Data is assigned a unique and consistent identifier to be found independently of the scientific area of research. Accessible: Data is described using a standardised communication protocol to make data accessible – even after data is no longer available. Interoperable: Data is compatible with a common language across research fields. Reusable: Data lives up to a range of quality standards in order to be readable – both for humans and machines.
Costs and benefits are compared against a cost-benefit approach based on the Ministry of Finance’s ’Vejledning i samfundsøkonomiske konsekvensvurderinger’ [Guidelines on socio-economic impact assessments]. Costs and benefits are estimated based on methods and key figures identified in the literature and supplemented with relevant statistics for the research activity in Denmark and considerations from interviews with key people in the research environment in Denmark and Germany (where work with FAIR principles have been conducted for a number of years). On this basis, the costs and benefits of introducing FAIR research data in Denmark are estimated over a 40-year period.
The preliminary analysis also examines the barriers and opportunities for implementing FAIR research data at the research institutions.
The analysis was carried out in collaboration with Oxford Research on behalf of the Ministry of Higher Education and Science.
Overall, the analysis indicates that there is a positive socio-economic value in introducing FAIR data in Denmark. In our basic scenario, we find that the socio-economic present value is approx. DKK 2 billion over a 40-year period, if 50% of all research data in Denmark is made FAIR. On average, this corresponds to an annual socio-economic gain of DKK 50 million. If all research data in Denmark is made FAIR, the present value will be just under DKK 4 billion.
The following costs and benefits have been analysed:
- Saved data work for researchers, value sets based on the researcher’s salary and the extra return that is obtained if the saved time is invested in another research activity instead.
- Creating new research or more efficient research with a higher return – this effect is not valued in the basic scenario as a precaution but can potentially be of great value.
- Start-up costs, e.g. building of metadata, workflow tools, policy etc.
- Operating costs, purchase and operation of servers and data access.
The positive socio-economic value of introducing FAIR data in Denmark requires that FAIR data, to a considerable extent, reduces the time that researchers spend on data work. Otherwise, the implementation of FAIR data could lead to socio-economic loss. The socio-economic value of FAIR data is thus very sensitive to this parameter, and it is therefore important to focus on obtaining as much efficiency gains as possible if you choose to introduce FAIR data in Denmark. Conversely, by introducing FAIR research data, the socio-economic value can be much greater if new research is created (which does not displace existing research) or if research is made more effective due to the opportunities offered by FAIR research data.
The result in our basic scenario is relatively robust, because the gains are approx. 40% greater than the cost. The return ratio shows that the investment in FAIR data (here measured at start-up costs) gives a socio-economic value of approx. half the investment, which is relatively low compared to return on investment (ROI) estimates for investment in data, library and information services. This is partly because our cost estimates are greater than similar analyses in the literature.
The study is commissioned by the Danish Agency for Science and Higher Education.
Højbjerre Brauer Schultz (2017): "Foranalyse: Indførsel af FAIR data i Danmark".