Abstract
A vast amount of Earth Observation data is produced daily and made available through online services and repositories. Contemporary and historical data can be retrieved and used to power existing applications, foster innovation, and improve EU citizens’ lives. However, the audience for this information is relatively small, resulting in vast amounts of valuable data remaining unexplored.
The EO4EU project aims to provide innovative tools, methodologies, and approaches that can assist a broad range of users, from domain experts and professionals to ordinary citizens, in benefiting from accessing EO data. It aims to deliver dynamic data mapping and labelling AI-augmented modules that add fairness to the data and introduce an ecosystem for the holistic management of EO data. EO4EU envisions bridging the gap between domain experts and end-users while bringing technological advances to the forefront to address the market's demand for wider usage of EO data.
The project will support the wider exploitation of EO data by delivering: (i) Machine Learning (ML) methodologies for Semantic Annotation of existing and growing data sources, (ii) semantically enhanced knowledge graphs that will enable structuring of content around diverse topic areas and building step by step journeys from different sources into a unified approach, (iii) data fusion techniques to extend the scalability of existing distributed systems, (iv) Augmented and Virtual Reality for interactive user experience, and (v) advanced data analytics visualisations for improved learning and evidence-based interpretations of environmental observations. Its operational and technical capacity will be demonstrated within seven distinct pilots that cover different thematic areas, such as personalized health care, sea route planning, ocean monitoring, food security, food ecosystems, soil erosion, environmental pest, and crisis management. These thematic areas will engage a wide spectrum of involved stakeholders, from EO providers, policy makers and actors, researchers and academics to citizen scientists and the general public to join efforts and provide their multidisciplinary expertise to support the Commission’s strategic goals towards further exploitation of EO data.
In this document, each of the seven use cases is analysed in detail to identify their data management needs, software component needs, and computational needs. Additionally, a summary of the deployment plan for each use case is presented, to consolidate it at a later stage against the data and processing infrastructure provider for technical alignment. These two chapters, namely the deployment plan and technical alignment, will be briefly described in this document, with more details to be provided in version B at a later stage.