Open research Europe · 2026
Mapping Non-Monetary Values in Data Sharing: Development and Validation of an SSH Framework Across Sectors.
СтатьяНазвание и аннотация: Перевод в очереди
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Hofer Margit, Fuchs Daniela, Vyhmeister Eduardo, Rausch Agnieszka
Аннотация
BACKGROUND: Data sharing is increasingly recognised as essential for innovation, sustainability, and resilience in Europe. However, existing frameworks primarily focus on technical and economic aspects, neglecting non-monetary values such as trust, ethics, cultural readiness, and organisational capacity. This study addresses this gap through the development and validation of a Social Sciences and Humanities (SSH) Framework for Data Sharing.
METHODS: A foresight-oriented, multi-method design combined a systematic literature review, interviews across six European pilots, and participatory foresight activities including visioning, backcasting, and feasibility assessment.
RESULTS: The analysis identified eleven SSH dimensions shaping data sharing: societal, ecological, security, scientific-research, macro-economic, customer-business, policy, ethics, cultural, organisational, and regulatory. Ethics, policy alignment, and scientific-research dimensions showed the highest feasibility across sectors, while cultural and societal dimensions consistently presented the greatest implementation challenges.
CONCLUSIONS: The SSH Framework offers an empirically grounded tool for designing inclusive and human-centric data governance. The results indicate strong alignment with EU data policy frameworks while revealing persistent sociocultural barriers. The Framework supports policy design by identifying priority areas for regulation, governance development, and capacity building at the EU, sectoral, and organisational levels, thereby contributing to the EU ambition of trustworthy and socially sustainable data spaces.
METHODS: A foresight-oriented, multi-method design combined a systematic literature review, interviews across six European pilots, and participatory foresight activities including visioning, backcasting, and feasibility assessment.
RESULTS: The analysis identified eleven SSH dimensions shaping data sharing: societal, ecological, security, scientific-research, macro-economic, customer-business, policy, ethics, cultural, organisational, and regulatory. Ethics, policy alignment, and scientific-research dimensions showed the highest feasibility across sectors, while cultural and societal dimensions consistently presented the greatest implementation challenges.
CONCLUSIONS: The SSH Framework offers an empirically grounded tool for designing inclusive and human-centric data governance. The results indicate strong alignment with EU data policy frameworks while revealing persistent sociocultural barriers. The Framework supports policy design by identifying priority areas for regulation, governance development, and capacity building at the EU, sectoral, and organisational levels, thereby contributing to the EU ambition of trustworthy and socially sustainable data spaces.