Mohr Matthias, Pebesma Edzer, Dries Jeroen, Lippens Stefaan, Janssen Bram, Thiex Daniel, Milcinski Grega, Schumacher Benjamin, Briese Christian, Claus Michele, Jacob Alexander, Sacramento Paulo, Griffiths Patrick
University of Münster, Institute for Geoinformatics, Münster, Germany.
VITO NV, Mol, Belgium.
Sci Data. 2025 Feb 1;12(1):194. doi: 10.1038/s41597-025-04513-y.
The unprecedented and continuously growing volume of Earth Observation (EO) and geospatial data has necessitated a paradigm change where compute is collocated with the data archives in public clouds. However, as no single cloud platform can host all of this data, federated processing solutions that work across multiple cloud platforms are becoming increasingly relevant. A community-based approach to federated processing has started using openEO, a common Application Programming Interface (API) and set of well-defined processes that simplifies reuse and provides a valuable level of abstraction when handling large EO data volumes. We present key concepts for federated processing and related interoperability aspects based on openEO Platform, a federated public cloud platform.
地球观测（EO）和地理空间数据量空前且持续增长，这就需要一种范式转变，即计算与公共云中的数据存档并置。然而，由于没有单个云平台能够承载所有这些数据，跨多个云平台运行的联合处理解决方案正变得越来越重要。一种基于社区的联合处理方法已开始使用openEO，它是一个通用的应用程序编程接口（API）和一组定义明确的流程，可简化重用，并在处理大量EO数据时提供有价值的抽象级别。我们基于联合公共云平台openEO Platform，介绍联合处理的关键概念及相关的互操作性方面。
