The main objective of EO4AGRI is to catalyze the evolution of the European capacity for improving operational agriculture monitoring from local to global levels based on information derived from Copernicus satellite observation data and through exploitation of associated geospatial and socio-economic information services. EO4AGRI assists the implementation of the EU Common Agricultural Policy (CAP) with special attention to the CAP2020 reform, to requirements of Paying Agencies, and for the Integrated Administration and Control System (IACS) processes. EO4AGRI works with farmers, farmer associations and agro-food industry on specifications of data-driven farming services with focus on increasing the utilization of EC investments into Copernicus Data and Information Services (DIAS). EO4AGRI addresses global food security challenges coordinated within the G20 Global Agricultural Monitoring initiative (GEOGLAM) capitalizing on Copernicus Open Data as input to the Famine Early Warning System Network (FEW-NET). EO4AGRI assesses information about land-use and agricultural service needs and offers to financial investors and insurances and the potential added value of fueling those services with Copernicus information. The EO4AGRI team consists of 11 organizations, complementary in their roles and expertise, covering a good part of the value-chain with a significant relevant networking capital as documented in numerous project affiliations and the formal support declarations collected for EO4AGRI. All partners show large records of activities either in Copernicus RTD, governmental functions, or downstream service operations. The Coordinator of EO4AGRI is a major industrial player with proven capacities to lead H2020 projects. The EO4AGRI project methodology is a combination of community building; service gap analysis; technology watch; strategic research agenda design and policy recommendations; dissemination (incl. organization of hackathons).

The digital transformation of food systems has entered a twilight zone: data-driven innovations have proven to be promising, but it is still unclear how to upscale adoption and have broader acceptance. The Data4Food2030 project aims to improve the data economy for food systems (DE4FS) by expanding its definition, mapping its development, performance and impact to create new insights and opportunities. This contributes to a more competitive and sustainable food system in the EU and supports implementation and adaptation of relevant policies such as a Digital Single Market, Green Deal and the Common Agricultural Policy. Data4Food2030 is a 4-year project that aims to 1) enlarge the knowledge base and insight into the DE4FS, 2) develop a system that monitors and evaluates the development, performance and impact of the DE4FS on relevant EU policies 3) identify drivers and barriers and turn these into opportunities, recommendations and solutions, 4) test solutions and evaluate recommendations in case studies and through stakeholder dialogues and 5) provide future scenarios and a roadmap and sustain the monitoring system to support policy development and accelerate the desired future state of the DE4FS. Data4Food2030’s approach is targeted at an improved future state of the DE4FS from which clear design principles, recommendations and solutions are derived for improving and adapting policies and practices at public and private level. As an essential part of the project, stakeholders are deeply engaged to provide input to various DE4FS concepts and evaluate several project outcomes to increase the impact of the project. Nine case studies provide real-life examples of the DE4FS at micro- and meso-economic level, deploying data and technologies, which are used for mapping and improvement to promote data-enabled business models. In this way, Data4Food2030 creates credible pathways to navigate properly through the twilight zone towards a fair, inclusive and innovative DE4FS.

STARGATEs contribution beyond state-of-the-art in applied climatic data solutions is the implementation of analytics models to support local and regional policy formulation and implementation related to mitigation on microclimate changes. Currently, policy making organizations predominantly utilize own data, typically limited to their own jurisdiction/administrative area. However, once the policy development process expands the evidence base and data sources beyond the traditional approach, there is need for global data. The addition of national, European and even global reference data sets for comparative analysis — including meteorological, climatic analysis, satellite data sources to improve decision making processes. The studies at landscape scale are required to understand leading ecological processes. The focus will be on Climate Smart Agriculture (CSA) and will extensively study the benefits of applying agri-environment-climate technical solutions to achieve sustainable agricultural development at landscape level. It means to support farm management modernization and at the same time get to know the underlying ecological factors that shape the farming landscape. STARGATE will leverage access to this data and also STARGATE climatic platform including developed models platforms to foster easy and affordable adoption by policy making bodies. The simples approach to decision support in policy development is effective visualization of data. Good visualization supports the policy developers’ in modelling sustainable policies and decisions. Unlike algorithmic simulation and modelling, visualization leaves the actual decision and assessment to a human user and thus provides an extra quality assurance before actual policy decisions are made. STARGATE provides innovative components for visualization of big data with a particular emphasis on geospatial visualization and advanced, dynamic charting.

Agriculture is a, literally, vital industry. Not only important for nourishment, but also a key determiant of health, economic and political stability; employment; business and biological ecosystems; and society. Because of its importance, most attention focuses on productivity but it is essential to have a global view in order to address environment sustainability problems. EUXDAT proposes an e-Infrastructure, which addresses agriculture, land monitoring and energy efficiency for a sustainable development, as a way to support planning policies. In order to do so, we need to address the problems related to the current and future huge amount of heterogeneous data to be managed and processed. EUXDAT builds on existing mature components for solving them, by providing an advanced frontend, where users will develop applications on top of an infrastructure based on HPC and Cloud. The frontend provides monitoring information, visualization, different parallelized data analytic tools and enhanced data and processes catalogues, enabling Large Data Analytics-as-a-Service. EUXDAT will include a large set of data connectors (UAVs, Copernicus, field sensors, etc.), for scalable analytics. As for the brokering infrastructure, EUXDAT aims at optimizing data and resources usage. In addition to a mechanism for supporting data management linked to data quality evaluation, EUXDAT proposes a way to orchestrate tasks execution, identifying whether the best target is a HPC center or a Cloud provider. It will use monitoring and profiling information for taking decisions based on trade-offs related to cost, data constraints, efficiency and resources availability. During the project, EUXDAT will be in contact with scientific communities, in order to identify new trends and datasets, for guiding the evolution of the e-Infrastructure. The final result of the project will be and integrated e-Infrastructure which will encourage end users to create new applications for sustainable development.