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Presentation Abstract eoAPI is a new, open-source, installable combination of data catalog and associated services for earth observation and related data with a cloud-computing infrastructure first approach. eoAPI combines STAC data ingestion, data hosting (pgSTAC), and querying services (stac-fastapi) with, raster (Titiler) and vector services (TiPg). eoAPI is built for reuse and has been used to power applications such as NASA’s VEDA Open Science Platform, the multi-agency Greenhouse Gas Center, MS Planetary Computer, and AWS ASDI’s data catalog and applications for International Federation of the Red Cross and MercyCorps. The SpatioTemporal Asset Catalog (STAC) specification provides a common language for earth observation (EO) data. STAC is used to power data discovery, visualization, train ML models, and perform Earth data science. By putting data into STAC, we can dynamically select parts of large catalogs of data, combine them together, and derive insights in multiple ways. . A wide range of open tools has made working and publishing with EO data at scale easier, however, the flexibility of the STAC specification makes it difficult for an organization to select which projects to choose, given their varying degrees of interoperability. eoAPI takes the work out of constructing a cloud-native EO infrastructure through an opinionated blueprint that will work well for most EO and geospatial infrastructure needs. eoAPI lowers the barrier to those who are both STAC-curious and STAC-serious. The presentation will cover eoAPI services, infrastructure as code, a demonstration of how the API is used and an explanation of eoAPI is reused across applications, as listed in the first paragraph. A developer with limited DevOps experience could deploy eoAPI. We believe we can do even better to make STAC catalogs and services on-demand and will share progress towards a 1-click deployment with attendees.
Earth Data, Open Science, Open Data, Data Science, AGU 2023, Dynamic Visualization, Earth Science, Cyberinfrastructure, Cloud Computing
Earth Data, Open Science, Open Data, Data Science, AGU 2023, Dynamic Visualization, Earth Science, Cyberinfrastructure, Cloud Computing
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