Abstract
EO4EU aims to further improve access to the EU EO data offered by a variety of platforms and data repositories. Data sources include Copernicus services and associate platforms like the DIAS, but also upcoming initiatives like Destination Earth (DestinE). Without prior knowledge about their structure and format, the platform shall be able to retrieve, process, fuse and deliver new datasets, supported by machine learning algorithms and advanced semantic annotations.
An innovative ML-based learned compression algorithms shall enhance the accessibility of the data sources by reducing the respective data volumes needs to be transferred over the network, reducing the footprint of storage capacity and the network bandwidth requirements.
The control and core plane components of the EO4EU platform adapts an event-driven and microservices-based architecture, hosted on the Platform as a Service (PaaS) Tier. PaaS platforms often integrate with Kubernetes to simplify microservices development, scaling, and management.
User Experience are further enhanced with a set of visualization services and interfaces, including a multi-layered user interface (GUI) for visual analytics coupled with a Workflow Editor, a Command Line Interface (CLI), and a respective Application Programming Interface (API), and an extended reality (XR) interface to further boost the usability and the adoption of the platform, combining traditional access methods with cutting-edge technology stack
All platform communications are handled through a message-based middleware (via a Message Bus). This provides a coherent communication model with distribution, replication, reliability, availability, redundancy, backup, consistency, and services across distributed heterogeneous systems.