Big Data

BDVA: Big Data Value Association

The Big Data Value Association AISBL is a fully self-financed non–for-profit organisation under Belgian law. The main role of the Big Data Value Association will be providing the Big Data Value strategic research agenda (SRIA) and its regular updates, defining and monitoring the metrics of the cPPP and joining the European Commission in the cPPP partnership board. The objectives of the Association are to boost European Big Data Value research, development and innovation and to foster a positive perception of Big Data Value. A basic principle is openness, transparency and inclusiveness. It aims at:  

  • strengthening competitiveness and ensuring industrial leadership of providers and end users of Big Data Value technology-based systems and services;
  • promoting the widest and best uptake of Big Data Value technologies and services for professional and private use;
  • establishing the excellence of the science base of creation of value from BIG DATA.



Big Data Finance

BigDataFinance 2015–2019, a H2020 Marie Sklodowska-Curie Innovative Training Network “Training for Big Data in Financial Research and Risk Management”, provides doctoral training in sophisticated data-driven risk management and research at the crossroads of Finance and Big Data for 13 researchers. The main objectives are:

i) to meet an increasing commercial demand for well-trained researchers experienced in both Big Data techniques and Finance

ii) to develop and implement new quantitative and econometric methods for empirical finance and risk management with large and complex datasets.



Big Data Europe: Empowering Communities with Big Data Technologies

H2020 societal challenges and their Big Data focus areas are health, food and agriculture, energy, transport, climate, societal changes and security. Big Data Europe will undertake the foundational work for enabling European companies to build innovative multilingual products and services based on semantically interoperable, large-scale, multi-lingual data assets and knowledge, available under a variety of licenses and business models. It aims to collect requirements for the ICT infrastructure needed by data-intensive science practitioners across all aspects and design and implement architecture for an infrastructure that meets requirements, minimizes the disruption to current workflows, and maximizes the opportunities to take advantage of the latest European RTD developments.

Link to the project’s flyer here.