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In the era of global challenges and big Earth data computation its becoming increasingly important to have proper interoperable solutions for describing, cataloguing, finding, accessing, and distributing highly valuable datasets. The usability and reproducibility of data under FAIR and GEO Data Sharing and Data Management Principles, with accurate description of datasets in terms of semantics and uncertainty, can make data more valuable. EC is pushing Data Spaces as a tool to manage data and generate and provide knowledge ready to use for managers and decision makers. The contribution presents a standard-based Data Space for automatically monitoring Water Quality specifically designed for European Lakes, based on remote sensing derived datasets, in-situ monitoring stations and web services. A web map browser gives access to water quality time series products (turbidity, Chl-a, floods, hydroperiod, etc) based on EO in Cloud Optimized GeoTIFF and in-situ observation stations connected using OGC STAplus standard. The map browser integrates the overall set of capabilities: data and metadata visualization, data analytics, quality indicators linked to the QualityML dictionary; semantic tagging of the Essential Water Variables; and OGC Geospatial User Feedback (GUF). The system is accessible through the OpenID-connect authentication standard which extends the OAuth 2.0 authorization protocol that allows different rights for different users to guarantee the preservation of data. This approach has been developed and tested under the Horizon 2020 WQeMS - Copernicus Assisted Lake Water Quality Emergency Monitoring Service (n 101004157). Some parts of the solution have been developed under the HORIZON-CL6 AD4GD - An Integrated, FAIR Approach for the Common European Data Space (n 101061001) co-funded by the European Union, Switzerland and the United Kingdom.
Serral et al. (Mon,) studied this question.