From Ethnography to Agent-Based Modeling: Tracing Knowledge Flows in Large Research Infrastructures and Stakeholder Networks

Abstract (English)

Large Research Infrastructures (LRIs) are embedded within expansive stakeholder networks, including government agencies, NGOs, industry partners, diverse public groups, scientists, engineers, and policymakers. They co-produce both fundamental discoveries and sustainable-development outcomes. We propose an integrative framework that combines rich, “thick” anthropological description with agent-based modeling (ABM) to trace the circulation of tacit skills, design principles, and problem framings across disciplinary, organizational, and geographical boundaries around LIRs. Ethnographic inquiry uncovers critical interactional modalities, through which collaboration cultures and Sustainable Development Goal–oriented objectives become embedded. These qualitative insights are formalized into an ABM that conceptualizes LRIs within multiplex stakeholder networks, enabling systematic exploration of how stakeholder choices, institutional arrangements, and collaboration norms jointly shape learning dynamics and knowledge transfer. By combining ethnography with ABM simulation, our framework offers a novel methodology for testing policy interventions and institutional designs that strengthen knowledge exchange and advance SDG realization within large-scale research ecosystems.