Abstract
Earth Observation (EO) data publication and dissemination continues to grow driven by the need to consistently monitor the earth in times of climate change. openEO is one of the most well known APIs to query and process EO data and is operationally available on many EO cloud platforms such as the Copernicus Data Space Ecosystem or Destination Earth. To be truly valuable, EO data often needs to be combined with other data sources, notably relational databases. Knowledge graphs offer a way to bridge the semantic gap between EO data and these other sources. An unsolved issue with this solution is that the execution of integrated queries can be costly due to the enormous volume of EO data. In this paper, we tackle this challenge through the use of Virtual Knowledge Graphs — a paradigm that presents data to end-users as a knowledge graph, while being kept its original sources and formats. Our approach is prototyped and evaluated against multiple real-world openEO examples.