FAIR (Findable, Accessible, Interoperable and Reusable) data principles stand out as critical to ensure that data can be efficiently shared and used across diverse scientific, academic, and industrial domains, facilitating interoperability and informed decision making. However, industrial players are often reluctant to embrace FAIR data principles due to reasons such as the fear of losing competitive advantage and the lack of resources to convert their datasets. This study is one of the few attempts to shed light on the advantages FAIR data can offer, highlighting adoption drivers and barriers with a focus on the aquaculture industry. The research is developed relying on a mixed methodology consisting of semi-structured qualitative interviews and quantitative questionnaires addressed to a selected group of relevant stakeholders. As a result of the study, six policy recommendations of political, technological, social and environmental nature are offered to outline a path towards a more sustainable and efficient aquaculture industry, supported by measurable KPIs to assess their impact. The results collected by this study stress the importance of available FAIR datasets across platforms. Perhaps more importantly, they allow the classification of the benefits of key circular economy (CE) and FAIR data management practices for the aquaculture sector, as well as current main adoption barriers and enablers. Key barriers include data acquisition costs, lack of skills and knowledge of FAIR data benefits, concerns and confusion with open data and lack of investments in interoperable solutions. In contrast, key enablers include cost reduction to acquire data, best-practice regulations, awareness of FAIR benefits, education to innovation, collaboration incentives and complexity reduction through standardised solutions. Although the timely implementation of this study’s final recommendation roadmap could favour impactful legislative changes to implement a more sustainable and efficient aquaculture sector, reliance on political will and targeted policymaking actions will in all likelihood delay their effective implementation.
This deliverable presents an overview of EOSC-related activities and projects that could be taken into account for the design and implementation of Competence Centres (CCs), positioned as key instruments to support data-intensive, FAIR-compliant, and interdisciplinary research within the European Open Science Cloud (EOSC). It synthesises existing practices, conceptual frameworks, and policy recommendations drawn from ongoing and past projects. CCs are understood by most of the research communities as decentralised, composable structures that may consolidate community expertise, support training and guidance for data sharing and reuse or provide embedded services across diverse research contexts. The deliverable outlines the different types of contributions of the domain-specific clusters. Each science cluster intends to align its CC strategies on either thematic priorities, governance approaches, training assets etc, and reflect on how they then could align within the OSCARS CC design and definition proposed in the framework of OSCARS WP1 (Bodera Sempere et al., 2024). The result of this landscaping highlights existing or in development principles, acknowledges heterogeneous implementations, foster cross-community learning and will lay the groundwork for a future inter-OSCARs project and inter-community paper on all kind of Competence Centres that can act in the framework of EOSC (discipline specific or thematic, local, regional, national…). The document identifies key interdisciplinary challenges such as multimodal data integration and large-scale metadata analysis emphasising the need for cultural change, capacity building, and embedded support mechanisms close to research practice, Challenges identified demand robust infrastructures, sustained collaboration, and the realisation of the “FAIR web of data,” a central EOSC ambition. The OSCARS CC model builds upon these insights to propose a federated and scalable ecosystem of competence. The models offer a practical roadmap to foster uptake, interoperability, and sustainability of Open Science across European research communities.
On 11 November 2025, SmartCHANGE hosted a webinar entitled "Putting Health Tools into practice: Designing feasibility studies at an international scale". The webinar showcased the implementation of SmartCHANGE’s AI-driven health tools, including the HappyPlant mobile app for families and the browser-based platform for healthcare professionals, teachers, and study administrators. Speakers from five international sites, including Ljubljana, Amsterdam, Porto, Jyväskylä, and Taipei, presented their study designs, recruitment strategies, local adaptations, early experiences, and lessons learned in deploying these tools across diverse settings. The full details of the event can be found of the official event page.
