FAIR data is a community effort – 10 years of RDNL and Dutch Data Prize
“The idea that a research community should come together and have a discussion about (and work on) common data standards has been around for decades.”
By Kimberley Zwiers and Samantha Willemsen
To celebrate 10 years of RDNL, we interviewed three winners of the Dutch Data Prize, which has been part of RDNL since 2013. What did the prize entail for them, why do they find FAIR data important and why should researchers nominate themselves for this prize? In the third edition of this three part series, we speak with Antica Culina. She is convinced that we should make a collaborative effort to make research data more FAIR, if we want to advance science.
As a researcher she quickly realized that we are not utilizing ecological research data to its full potential. “The idea that a research community should come together and have a discussion about (and work on) common data standards has been around for decades.”, says Culina. With the SPI-Birds Network & Database, which connects researchers that study the populations of breeding, individually marked birds, those ideas were finally put into action. In 2020, she and Marcel Visser won the incentive prize in the Dutch Data Prize category Life Sciences and Health (LSH) with their SPI-Birds initiative. “Participating in the Dutch Data Prize was a great experience, as it gave us an opportunity to have someone objectively evaluate our work and it encouraged us to continue the work that we were already doing. It was nice to receive recognition for all the work we have been doing thus far and also proved to be an excellent networking opportunity.” says Antica Culina, who works as a senior research fellow at the Ruder Boskovic Institute in Croatia and is an honorary fellow at NIOO-KNAW. Culina is also a large advocate for open science, and participates in many open science initiatives such as EOSC, SORTEE, RDA, GoFAIR discovery IN, UNESCO Open Science, Open Knowledge Maps, and FAIRsFAIR.
We need to do better, if we want to advance science
The awareness of and importance for researchers to contribute to open science or to make their data FAIR is rapidly increasing. However, some are still resistant, claiming that data management is too time consuming, consequently financially costly and are afraid that it will diminish publication output. We asked Culina on her perspective on this, she remarks:
“Making data FAIR is not the same as making them Open”. Making your data FAIR makes it easier for yourself to use or analyze the data at a later stage. Once the data is FAIR, you decide who you share your data with or who you collaborate with inside and outside your organization. Making data FAIR prevents the loss of data and enables reuse of data. Describing your data with rich metadata improves the visibility and findability of your research project by other researchers and the wider public.” Thus, making data FAIR actually saves time and can increase the number of collaborations, and rate or quality of your publication output.” It is important to organize your data even when the immediate applications for it are not clear yet, as it allows us to act fast when new developments in the field arise and we imminently do need the data (e.g. Covid). “Hence, we should not force openness, but rather support FAIRness. If we want to advance science, we need to be transparent about our data, learn from our mistakes by letting other researchers point out the flaws in our datasets and make sure we do better in the future, and enable other to use our data.” It is time that we stop being afraid and instead start embracing open science.
Another interesting remark was made by Culina with regards to funding initiatives such as SPI-birds: “The lack of funding is really an obstacle to initiatives such as SPI-birds. When applying for traditional science funding, the project needs to have a research or scientific aspect. Initiatives such as SPI-birds do not fall into this category, as they are often not considered as research initiatives, but rather as technical initiatives. On the other hand, projects such as SPI-Birds are considered too small for larger open science related funds (e.g. EOSC) that would support a project over longer time. This really limits the support and growth opportunities of initiatives such as SPI-birds”. Statements like these underline the importance of another discussion that we collectively should have, i.e. how are we going to sustain upcoming or existing open science initiatives and safeguard them for future generations?
Read part one of the three part series here: An interview with Maarten Marx. One of the first winners of the Dutch Data Prize. Part two you can find here: an interview with Joaquin Vanschoren, who won the prize at a crucial moment in his career.
The Dutch Data Prize is part of Research Data Nederland (RDNL), a consortium existing of 4TU.ResearchData, DANS, Health-RI and SURF. The next round of the Dutch Data Prize will be held in 2024.
