POSE: Phase I: Building an Open-Source Ecosystem for Spatial Multi-Scale and Multi-Omics Data Science

Award ID: 2612076

This project will support the transition of the Giotto Suite an established software platform for analyzing spatial omics data into a sustainable, communityled OpenSource Ecosystem (OSE). Spatial omics techniques allow scientists to study the molecular makeup of tissues while preserving their physical structure. Progress studying such tissues has been hindered by fragmented data formats and workflows that differ widely across research laboratories. Supported by the Pathways to OpenSource Ecosystems (POSE) Program, this effort will help unify the community around shared standards, inclusive governance, and accessible tools that promote collaboration across academic, clinical, and industry environments. By identifying barriers to participation and strengthening community infrastructure, the project will make advanced data science tools more accessible and easier to use. Spatial omics is important because it reveals how cells behave within their native tissue environment, preserving the spatial relationships that drive health and disease. These techniques provide insights that enable more precise diagnostics, better therapeutic targeting, and deeper understanding of complex biological systems. The project will carry out a threestage evaluation framework audit, consultation, and synthesis to determine the technical, organizational, and social infrastructure needed for the Giotto Suite to become a scalable OSE. The audit stage will benchmark current performance and identify exit points where users leave the platform, while the consultation stage will gather input from global stakeholders through surveys, interviews, and a fourday hybrid community planning lab. The synthesis stage will integrate these findings to draft a technical charter and propose governance and interoperability structures for a communitymaintained ecosystem. Throughout this scoping process, the project will assess needs across diverse research environments and define standards that support multiomics and multiscale data integration. The resulting roadmap will guide the longterm transition into a robust, interoperable, and communityvalidated opensource platform. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Florence Rabanal