Large raster datasets are central to earth observation, climate research, environmental monitoring, and public-sector data services. Yet they are often published as files that are hard to discover, compare, cite, or reuse without knowing the exact storage location, format, and processing tools in advance.
raster2stac is a Free Software Python library that helps turn existing raster datasets into structured, standards-based data products. It creates SpatioTemporal Asset Catalogs (STAC) Collections, Items, and Assets from formats such as netCDF, Cloud Optimized GeoTIFF, and Zarr, so datasets can be described consistently and accessed through common open geospatial tools.
STAC is now an OGC Community Standard and is widely used in the earth observation ecosystem, including by major public data providers and platforms such as Copernicus Data Space Ecosystem and the NASA Earthdata. This makes it a practical bridge between local data publishing workflows and the broader open geospatial infrastructure used by researchers, public institutions, and service providers.
In this lightning talk, I will show the problem raster2stac addresses, the publishing workflow it enables, and why this matters for digital sovereignty. The focus is not only on converting files, but on making scientific and public geospatial data more findable, interoperable, reusable, and less dependent on vendor-specific platforms or custom data portals.
The audience will leave with a practical understanding of how open standards such as STAC, combined with Free Software, can help institutions publish raster data in a way that is easier to share, automate, preserve, and build upon.
