Big data is becoming a hype that is going to completely redefine industries within very traditional sectors like agriculture, food and beauty. The emergence of niche big data companies like Enolytics (“bringing big data insights to the wine industry”) is threatening to disrupt these industries against the interests of the EU. BigDataGrapes wants to build upon the rich historical, cultural and artisan heritage of Europe in order to change this picture. It aims to support all European companies active in two key industries powered by grapevines: the wine industry and the natural cosmetics one. It will help them respond to the significant opportunity that big data is creating in their relevant markets, by pursuing two ambitious goals: a. To develop and demonstrate powerful, rigorously tested, cross-sector data processing technologies that go beyond-the-state-of-the-art towards increasing the efficiency of companies that need to take important business decisions dependent on access to vast and complex amounts of data, and assess them in challenges informed by the grapevine-powered industries. b. To create a large-scale, mulifaceted marketplace for grapevine-related data assets, increasing the competitive advantage of companies that serve with IT solutions these sectors and helping companies and organisations evolve methods, standards and processes to help them achieve free, interoperable and secure flow of their data. BigDataGrapes is targeting technology challenges of the grapevine-powered data economy as its business problems and decisions requires processing, analysis and visualisation of data with rapidly increasing volume, velocity and variety: satellite and weather data, environmental and geological data, phenotypic and genetic plant data, food supply chain data, economic and financial data and more. It therefore makes a perfectly suitable cross-sector and cross-country combination of industries that are of high European significance and value.

Recent years witness an upsurge in the quantities of digital research data, offering new insights and opportunities for improved understanding. Text and data mining is emerging as a powerful tool for harnessing the power of structured and unstructured content and data, by analysing them at multiple levels and in several dimensions to discover hidden and new knowledge. However, text mining solutions are not easy to discover and use, nor are they easily combinable by end users. OpenMinTeD aspires to enable the creation of an infrastructure that fosters and facilitates the use of text mining technologies in the scientific publications world, builds on existing text mining tools and platforms, and renders them discoverable and interoperablethrough appropriate registriesand a standards-based interoperability layer, respectively. It supports training of text mining users and developers alike and demonstrates the merits of the approach through several use cases identified by scholars and experts from different scientific areas, ranging from generic scholarly communication to literaturerelated tolife sciences, food and agriculture, and social sciences and humanities. Through its infrastructural activities, OpenMinTeD’s vision is tomake operational a virtuous cycle in which a) primary content is accessed through standardised interfaces and access rules b) by well-documented and easily discoverable text mining services that process, analyse, and annotate text c) to identify patterns and extract new meaningful actionable knowledge, which will be used d) for structuring, indexing, and searching content and, in tandem, e) acting as new knowledge useful to draw new relations between content items and firing a new mining cycle. To achieve its goals, OpenMinTeD brings together different stakeholders, content providers and scientific communities, text mining and infrastructure builders, legal experts, data and computing centres, industrial players, and SMEs.

CYBELE generates innovation and create value in the domain of agri-food, and its verticals in the sub-domains of PA and PLF in specific, as demonstrated by the real-life industrial cases to be supported, empowering capacity building within the industrial and research community. Since agriculture is a high volume business with low operational efficiency, CYBELE aspires at demonstrating how the convergence of HPC, Big Data, Cloud Computing and the IoT can revolutionize farming, reduce scarcity and increase food supply, bringing social, economic, and environmental benefits. CYBELE intends to safeguard that stakeholders have integrated, unmediated access to a vast amount of large scale datasets of diverse types from a variety of sources, and they are capable of generating value and extracting insights, by providing secure and unmediated access to large-scale HPC infrastructures supporting data discovery, processing, combination and visualization services, solving challenges modelled as mathematical algorithms requiring high computing power. CYBELE develops large scale HPC-enabled test beds and delivers a distributed big data management architecture and a data management strategy providing 1) integrated, unmediated access to large scale datasets of diverse types from a multitude of distributed data sources, 2) a data and service driven virtual HPC-enabled environment supporting the execution of multi-parametric agri-food related impact model experiments, optimizing the features of processing large scale datasets and 3) a bouquet of domain specific and generic services on top of the virtual research environment facilitating the elicitation of knowledge from big agri-food related data, addressing the issue of increasing responsiveness and empowering automation-assisted decision making, empowering the stakeholders to use resources in a more environmentally responsible manner, improve sourcing decisions, and implement circular-economy solutions in the food chain.

The strategic goal of e-ROSA is to provide guidance to EU policies by designing and laying the groundwork for a long-term programme aiming at achieving an e-infrastructure for open science in agriculture that would position Europe as a major global player at the forefront of research and innovation in this area. Through a foresight approach, the project will build a shared vision of a future sustainable e-infrastructure for research and education in agriculture and make it operable through pragmatic recommendations that will be reflected in a common roadmap. This will be achieved through a process of co-design, involving mainly research and education communities but also practitioners and EU policy makers, and will build on the existing projects, networks, international alliances or initiatives that the project will systematically map and integrate in the analysis of grand challenges ahead and the identification of priorities and solutions towards an open, digital and data-intensive science in agriculture.

The overall objective of HOLiFOOD is to improve the integrated food safety risk analysis (RA) framework in Europe to i) meet future challenges arising from Green Deal policy driven transitions in particular in relation to climate driven changes, ii) contribute to the UN's Sustainable Development Goals and iii) support the realization of a truly secure and sustainable food production. HOLiFOOD will apply a system approach, which take the whole environment into account in which food is being produced, including economic, environmental and social aspects. Three supply chains will be considered (i.e. cereals [maize], legumes [lentils] and poultry [chicken]). Artificial Intelligence (AI) and big data technologies will be used in the development of early warning and emerging risks prediction systems for known and unknown food safety hazards. In addition, tools, methods and approaches will be developed for hazard detection and will be targeted and non-targeted and new holistic risk assessment methods will be develop in which food safety risk will be embedded in a comprehensive cost-benefit analysis of the food system including positive and negative health, environment and economic dimensions. An effective impact pathway will be developed and implemented through integration of the HOLiFOOD outputs into the legal framework associated with the food risk analysis process. The impact pathway will be supported by an electronic data and knowledge sharing platform aiming at the full digitalization of food (safety) systems and supporting transparency and impact for all stakeholders. In order to align with stakeholder priorities, preferences and user requirements, the HOLiFOOD innovations will be designed and tested in a multi actor approach (i.e. Living Lab) involving all stakeholders (e.g., authorities, food producers and citizens).