Computational Modelling of Health Data Statement of Work

This Computational Modelling of Health Data Working Group aims to establish a curated, community-driven resource to support the development and dissemination of computational models in health research. It will provide detailed guidance on how to develop models using appropriate inputs related to health research domain —such as data features, synthetic and simulated datasets, open-source software, and parameters—ensuring reproducibility and accessibility. By consolidating best practices, standard protocols, and examples across a range of model types including simulation, statistical, machine learning, and large language models, the group will support users in creating transparent and reusable workflows in health research.

The resource will be particularly valuable in data-scarce environments, where high-quality synthetic datasets and standardised tools can accelerate research while reducing development time. It addresses challenges in computational  health research including lack of reproducible workflows, inconsistent data preparation practices, and the perception of computational models as opaque “black boxes”.

Target audiences include clinicians, biomedical researchers, data scientists, policy-makers, and software developers. Engagement with existing RDA groups and other relevant initiatives will ensure alignment with ongoing global efforts. Through workshops, collaborative writing sessions, and stakeholder outreach, the group will foster adoption and real-world application.