DeepCube leverages advances in the fields of AI and semantic web to unlock the potential of big Copernicus data. DeepCube is impact driven; our objective is to address new and ambitious problems that imply high environmental and societal impact, enhance our understanding of Earth’s processes, correlated with Climate Change, and feasibly generate high business value. To achieve this we bring mature and new ICT technologies, such as the Earth System Data Cube, the Semantic Cube, the Hopsworks platform for distributed DL, and a state-of-the-art visualisation tool tailored for linked Copernicus data, and integrate them to deliver an open and interoperable platform that can be deployed in several cloud infrastructures and HPC, including DIAS environments. We then use these tools to develop novel DL pipelines to extract value from big Copernicus data. We implement a shift in the use of AI pipelines. DeepCube 1) develops novel DL architectures that extend to non-conventional data and problems settings, such as interferometric SAR, social network data, and industrial data, 2) introduces a novel hybrid modeling paradigm for data-driven AI models that respect physical laws, and 3) opens-up the DL black box through Explainable AI and Causality. We showcase these in five Use Cases (UC), two business, two on earth system sciences, and one for humanitarian aid. These are: UC1: Forecasting localized extreme drought and heat impacts in Africa, UC2: Climate induced migration in Africa, UC3: Fire hazard short-term forecasting in the Mediterranean, UC4a: Automatic volcanic deformation detection and alerting and UC4b: Deformation trend change detection on PSI time-series for critical infrastructure monitoring, UC5: Copernicus services for sustainable and environmentally-friendly tourism.

Copernicus is the European program for monitoring the Earth. The geospatial data produced by the Sentinel satellites puts Copernicus at the forefront of the Big Data paradigm, giving rise to all the relevant challenges: volume, velocity, variety, veracity and value. ExtremeEarth concentrates on developing the technologies that will make Europe a pioneer in the area of Extreme Earth Analytics i.e., the Remote Sensing and Artificial Intelligence techniques that are needed for extracting information and knowledge out of the petabytes of Copernicus data. The ExtremeEarth consortium consists of Remote Sensing and Artificial Intelligence researchers and technologists with outstanding scientific track records and relevant commercial expertise. The research and innovation activities undertaken in ExtremeEarth will significantly advance the frontiers in Big Data, Earth Analytics and Deep Learning for Copernicus data and Linked Geospatial Data, and make Europe the top player internationally in these areas. The ExtremeEarth technologies will be demonstrated in two use cases with societal, environmental and financial value: the Food Security use case and the Polar use case. ExtremeEarth will bring together the Food Security and Polar communities, and will work with them to develop technologies that can be used by these communities in the respective application areas. The results of ExtremeEarth will be exploited commercially by the industrial partners of the consortium.

HEAP will provide a research resource for the integrated and efficient analysis of the human exposome. One primary outcome of the project is the complete process for obtaining actionable knowledge from the following sustainable cohorts: 1) a nation-wide Maternity Cohort where the impact of exposures on the health of women and children is supported by measures from wearable exposure sensors and metabolomics analysis, 2) a large cervical screening cohort enabling studies on women´s health supported with systematic epigenomics and metagenomics analyses, 3) and the systematic collection of consumer purchasing receipts linked to health outcomes will open new possibilities for assessing the impact of exposures on health in households. HEAP will launch a state-of-the-science informatics infrastructure (IaaS) composed of prime ICT resources from partner institutions in several EU countries, accessed through a software platform (PaaS) that includes the world’s fastest Hadoop platform to provide data warehousing and applied AI. The platform customised for exposome assessment will provide a decision support system for researchers, policymakers, and industry. All the data managed and processed by HEAP will be available for future research as well as the developed analyses. The platform can be enriched with new data and analysis pipelines and can be deployed in multiple instances to create a HEAP network towards producing shareable and reusable knowledge to promote health in society. HEAP will be under the umbrella of the European Human Exposome Network and will actively commit to collaboration and sharing of results and outcomes as well as contribute to i) a common ethical and regulatory framework, ii) common standardization and FAIRness of exposome data and iii) common dissemination strategies and efforts.