Symposium "Digital Twins of Organisms and their Environment"
October 8th, 2026, Studio Paraiso, Utrecht
The increasing availability of large and diverse datasets is creating unprecedented opportunities to develop digital twins of biological and ecological systems. Across fields, initiatives are emerging to integrate data, models, and observations into digital representations. Such digital twins are detailed virtual replicas of a real life phenomenon, which can be used to monitor performance, simulate scenarios, and predict issues before they happen in reality, for instance to design new hypotheses and avoid unnecessary testing.
Constructing digital twins remains challenging. Key obstacles include integrating heterogeneous data sources, developing and adopting appropriate ontologies, ensuring interoperability between databases and platforms, and maintaining data quality and reproducibility. At the same time, rapid advances in machine learning and generative AI offer new opportunities to automate data integration, extract knowledge from disparate sources, and accelerate model development.
This meeting organized by NWO Research Community 3 (RC3) “Organisms in their environment” aims to bring together researchers working on digital twins across a wide range of fields, from ecology and evolutionary biology to behavioural biology and related disciplines. By sharing experiences, challenges, and solutions, we hope to identify common themes and explore the extent to which approaches developed in one domain can be transferred to others.
Topics of interest include, but are not limited to:
Data integration and interoperability
Ontologies and semantic frameworks
Machine learning and AI-assisted workflows
Data standards, FAIR principles, and reproducibility
Cross-disciplinary lessons and transferable solutions
Confirmed speakers: Marcel Visser (NIOO-KNAW), Jorge Meijas (UvA), Sharif Islam (Naturalis)
The meetings is open to all. If you are interested in give a short pitch or presentation, please contact the organizers at rescom.oite@gmail.com.