The CALLISTO knowledge graph represents various domains of knowledge addressed within the EU-funded CALLISTO project. CALLISTO aims to bridge the gap between Copernicus Data and Data and Information Access Service (DIAS) providers and users in different domains by providing AI solutions that effectively add value to large amounts of satellite data. The project focuses on the Earth Observations (EO) domain and its relationship with four Pilot Use Cases (PUCs): 1) Common Agricultural Policy (CAP) monitoring, 2) water quality assessment, 3) air quality assessment and journalism, and 4) land border surveillance. Each PUC addresses a particular domain and contributes multiple datasets to the project, which come in diverse formats (e.g., XML, JSON, CSV). The CALLISTO ontology has been developed to handle this multi-domain data by offering a semantic representation of each domain and the connections between them. The knowledge graph was then generated by mapping the PUCs datasets to the ontology using RDF Mapping Language (RML). Knowledge graphs aid in linking data from various domains, generating new knowledge, and inspecting recurring patterns that can be used in simulation and prediction models (i.e., using artificial intelligence and deep learning algorithms). Another benefit of employing KGs is the ability to link them to other Linked Open Data (LOD) for data integration and analytics. Applications such as geospatial question answering, geospatial data retrieval, and cross-domain semantic data-driven applications could use it as an underlying data source. The CALLISTO knowledge graph is available in an RDF format; it is associated with the CALLISTO ontology. For further details about the ontology, please refer to deliverable D6.1: The CALLISTO ontologies and semantic indexing. The ontology and knowledge graph were developed by the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS). In collaboration with PUC members, the ontology and knowledge graph were developed and evaluated.