GeoEDF: Extensible Geospatial Data Framework towards FAIR (Findable, Accessible, Interoperable, Reusable) Science

Scientists in geospatial data-driven fields often spend significant efforts in “wrangling data”, i.e., accessing and processing data to make them usable in modeling and analysis tools. This project has created GeoEDF, an extensible geospatial data framework, to reduce this barrier by creating seamless connections among platforms, data and tools, making large distributed geospatial datasets directly usable in models and tools. Through an extensible set of community-contributed, modular and reusable data connectors and processors, GeoEDF abstracts away the complexity of acquiring and utilizing remote datasets. Researchers can string them together into a workflow for execution in various environments including a well-established science gateway MyGeoHub, JupyterHub-based deployments, and as a Docker container on laptops. By bringing data to the science, GeoEDF helps accelerate data-driven discovery and improve FAIR science practices.