AD4GD demonstrated how to create semantically enriched formats in an automatic way applying vocabularies and data model schemas. When relevant concepts cannot be found in existing vocabularies, the OGC RAINBOW is used to import and organize these concepts, as done in the Essential Biodiversity Variables. Other domains scientists can read the enriched data, interpret the variable definitions, and units of measure added to the numerical or categorical values of the observations and know the meaning of the data. In-situ data can subsequently be exported automatically as a Sensor Things API (STA) service. Searching in a semantically enriched data catalogue coming from the official sources as well as Citizen Science, Artificial Intelligence models can find datasets that are useful for training data. AD4GD has adopted the OGC API Coverage standard to represent datasets organized as multidimensional data cubes.
The results were exposed in standards from the International Data Space Association (also implemented by the SIMPL platform). We deployed the current version of the Eclipse Dataspace Connector (EDC) to create a prototype of the GDDS. AD4GD, USAGE and FAIRiCUBE projects, connected 3 instances allowing secured file exchange of data among the 3 projects, including static files and OGC APIs query results. It is expected that these 3 EDC nodes, and the semantic uplift mechanism, constitute the embryo of a future GDDS the SAGE project will deploy in the next 2.5 years. AD4GD explored alternative solutions for the exchange of restricted data in a data space, such as FACTS smart certificates for immutable assets.
To demonstrate approaches to zero pollution in water reservoirs, AD4GD selected Berlin’s small lakes. This pilot tested strategies for measuring water quality using remote sensing, deployed new in-situ oxygen sensors, experimented with algorithms that detect lakes in need of urgent interventions and implemented a ML model to predict water quantity based on three different scenarios of rain intensity. Terrestial habitat connectivity affects the distribution of species within ecosystems. AD4GD conducted a pilot to accelerate the computation of connectivity indices by combining data coming from remote sensing maps, species occurrence observations (some contributed by citizens) and sensor data to enhance regional and local actions. Poor urban air quality causes serious health issues across Europe. The results demonstrate that the resolution of the Copernicus Atmosphere Monitoring Service (CAMS) can be improved in cities by including Citizen Science air quality sensors collected by communities such as the Sensor.Community network.
