Big Data technologies and extreme-scale analytics
a) Research and Innovation Actions developing new big data analytics methodologies and engineering solutions addressing industrial and/or societal challenges. Proposals may cover (but are not limited to): architectures for collecting and managing vast amounts of data; system engineering/tools to contribute to the co-design of secure federated/distributed systems (to involve all stakeholders/technology areas); new methods for extreme-scale analytics, deep analysis, precise predictions and decision making support; novel visualization techniques; standardized interconnection methods for efficient sharing of heterogeneous data pools, seamlessly using distributed tools and services.
The data assets should be available to the project and described in the proposal. The Commission considers that proposals requesting a contribution from the EU of between EUR 3 and 6 million would allow this area to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.
b) One CSA to ensure coordination between the different existing activities in HPC/BD/Cloud technologies, including Public-Private Partnerships, digital innovation hubs, and relevant national and regional initiatives, in particular the European Network of National Big Data Centres of Excellence[[http://i-know.tugraz.at/european-network/]].
The Commission considers that proposals requesting a contribution from the EU of EUR 1 million would allow this area to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.
All grants under this topic will be subject to Article 30.3 of the grant agreement (Commission right to object to transfers or licensing).
Rapidly increasing volumes of diverse data from distributed sources create challenges for extracting valuable knowledge and commercial value from data. This calls for novel methods, approaches and engineering paradigms in analytics and data management. As the success will require not only efficient data processing/management but also sufficient computing capacity and connectivity, a coordinated action with all related areas (e.g. analytics, software engineering, HPC, Cloud technologies, IoT) is necessary and will contribute to a European leadership in these areas.
a)
- Increased productivity and quality of system design and software development thanks to better architectures and tools for complex federated/distributed systems handling extremely large volumes and streams of data;
- Demonstrated, significant increase of speed of data throughput and access, as measured against relevant, industry-validated benchmarks;
- Demonstrated adoption of results of the extreme-scale analysis and prediction in decision-making (in industry and/or society)
b)
- Effective cooperation of the participating initiatives and platforms as measured by the jointly participating members/users, countries/regions/cities and projects, and the organisation of common events and joint initiatives, resulting in an increased prevalence of data value chains and related technologies (HPC/BD/Cloud/IoT) in the national and regional strategies.