COST: Challenges and solutions for data sharing in different research fields

On 23 September 2024, as part of the Science Summit at the 79th United Nations General Assembly (UNGA79), COST co-organised the session ‘Hurdles to International Science Cooperation: Data Sharing & Management’ with the U.S. National Science Foundation’s AccelNet program.

Data sharing in research networks and for international collaboration raise several key questions for scientists and researchers. Data have become an object of public interest that needs the development of norms on sharing, accessibility, and use of data.

Data management in research networks: three key questions

Speakers from both COST Actions and AccelNet’s came together to emphasise, through the lens of their research network and experience, how data can become shareable and open to serve the research purpose in an international collaborative context.

Challenges and solutions

What do archaeologists, AAL professionals, astrophysicists, grape genome experts, lawyers, oceanographers, environmental chemists, and specialists in earth observation have in common? Data sharing and open collaboration on research data hiders their research process and progress in their respective fields.

Discover the challenges and solutions experiences by our researchers in their respective fields when it comes to data sharing, and what solutions their COST Actions and AccelNet projects are promoting:

Why is collaboration important?

International collaboration for data sharing is critical to advance science. But collaboration can lead to diverse results and serve different end goals for our research networks.

Legislation, competition and artificial intelligence

Panelists discussed some of the more unforeseen impacts of the General Data Protection Regulation (GDPR) legislation on their research fields when it comes to research data and sharing. Holly Wright shared the interesting example that archeologists are at risk of losing photographic evidence of the history of archeological exploration as you cannot include images of people doing archaeology in reports as historical consent to use these photos does not exist. Pending questions remain on how you manage consent especially when using genomic data, for example how to maintain consent when you want to reuse the data for something else related but five years later.

The researchers reflected on the tension that exist when you want to be really open and share your data but at the same time it’s hard to ignore the competitivity that exists within your field and different research groups. How can you be open and welcoming but still protect your own research interests? “Climate change might be a great opportunity to help us overcome data sharing challenges. This problem is bigger than you and I, and it forces us to come together. We should look at shared problems that can unite us to try to solve them” shared Abu Mansaray.

The event closed with an exchange on how artificial intelligence is changing data sharing views and practices. Encouraging data holders and nations to open their data can be problematic, which is a barrier when researchers need huge quantities of data to train and create AI models. The panelists shared positive examples of data holders granting access to data for AI model training purposes without having the navigate the slow process and challenges of ‘opening’ data officially. Meanwhile the panelists support sharing all data and code openly to help ensure ‘good’ AI algorithms are used and not random ones that misinterpret the data.

The session was an opportunity to address these challenges that require a multi- faceted approach.  It includes improved policies, incentives for data sharing, technical solution solutions, and a cultural shift towards more open collaborative research practices.

This article was first published on 23 September by COST association.