AD4GD D2.4 Citizen Science Data Interoperability Obstacles and Solutions (final)

As part of the European Data Strategy, the European Commission (EC) is working towards establishing a Green Deal Data Space (GDDS) that covers issues such as climate change, circular economy, pollution, biodiversity and deforestation. The EC recognises the increasing importance of including citizen-generated data into political decision-making and as such integrating citizen science data into the GDDS. To be fit for integration, citizen-generated data will need to comply to FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles. Research however shows that data sharing practices in citizen science projects are often inconsistent, presenting challenges for data interoperability and integration at larger scales.

This document is the Deliverable 2.4 for the AD4GD project. It presents the results achieved in the context of Task 2.3 “Defined co-design methodologies for CitSci for Green Deal topics and facilitated convergence to a common semantics”. The document is a follow-up version of the Deliverable 2.3 “CitSci Data Interoperability Obstacles and Solutions” that presented the outcomes of Task 2.2 “Identification of CitSci data including complementary socioeconomic and INSPIRE data”.

Task 2.2 aimed to investigate the state of play with citizen science data in regard to FAIR compliance by examining citizen science platforms, tools, and prominent initiatives. Building on the results, Task 2.3 focused on engaging with real-world citizen scientists, citizen science projects, and citizen science experts.

Participatory approaches were designed in this project to take account of and incorporate the views of citizen scientists and citizen science experts in the future development of the GDDS. Our research aimed to (a) extract first-hand knowledge on real world data management practices, (b) obtain views on FAIR and the GDDS initiative, and (c) employ co-design activities to collaboratively identify key obstacles in citizen science data journey and collectively generate ideas on potential ways to address them.