Ecological research increasingly relies on the integration of heterogeneous knowledge sources, including field observations, experimental results, theoretical models, and socio-economic data. However, relevant knowledge remains highly fragmented across disciplines, conceptual frameworks, and data infrastructures, which limits the capacity for ecological synthesis. Recent advances in large language models, semantic knowledge graphs, and agent-based AI systems make it technically feasible to formalize and computationally integrate ecological and social-ecological knowledge. Yet the conceptual, methodological, and epistemological foundations required for such integration remain largely unresolved. Without addressing these issues, AI-based synthesis risks producing scientifically unreliable or non-interpretable results. Initial progress on these issues has emerged from recent interdisciplinary collaborations, including a  research group at the Center for Interdisciplinary Research (ZiF) in Bielefeld, which brought together scholars from ecology, computer science, and philosophy of science, among them the organizers of this workshop.

The workshop will therefore bring together an international group of researchers and structure an emerging research field on integrative social-ecological knowledge systems.