This section includes two additional tools provided by our partners including: 

  • MELODI-CANDELA tool, you can have access to several contributions to CANDELA WP2.

These contributions, which are available here, can be resumed in three-folds:

  1. Ontologies and sample queries: we present the developed and archived ontologies for EO data integration: Sentinel2 image meta-data ontology ( , weather forecast data ontology ( ) , ontology for EO data resulting from image processing ( , territorial observation ontology ( ). Several sample queries are proposed to discover the integrated semantic data.
  2. Semantic search and query tools ( ): We present the semantic search architecture. The semantic search web interface is cloned and available as a demonstrator. Additional tools helping query our endpoints are also available.
  3. Use cases demonstration ( We briefly present the use cases and the results of semantic search.

Besides that, the public can access our repositories for source code and docker images. References to the publications associated with the project are also given.

  • DLR-CANDELA tool, which has been describes in numerous documents and video contents as the follows:
  1. CANDELA EO Data Mining Tools: A tutorial video which describes all technical details and shows how this tool works. The video presentation was realized by our partner Mihai Datcu (DLR, Germany) regarding Machine Learning principles with a focus on Active Learning implementing EO Data Mining functions. You can see the full video here.
  2. Data Fusion is analysing jointly Sentinel-1 (S-1) and Sentinel-2 (S-2) images and implements functions for classification and semantic annotation of Earth cover structures. The Data Fusion (DF) component is based on the main Data Mining modules with the following Data Fusion implementation: Data Model Generation (DMG-DF), Data Base Management System (DBMS), Image Search and Semantic Annotation (ISSA). More details in terms of Data Fusion has been described in this document D2.8.
  3. Data Mining implements functions for exploration, information and semantic extraction from large collections of EO products. It is a Big Data EO image and metadata mining process augmented with Machine Learning (ML) techniques, and the extracted information is interoperable with the other CANDELA or external non-EO data. More details in terms of Data Mining has been described in this document D2.2 including the user manual (see chapter 4).