Community Research and Development Information Service - CORDIS

ExpectedImpact:

a. Coordination and Support action

  • At least 10 major sectors and major domains supported by Big Data technologies and applications developed in the PPP;
  • 50% annual increase in the number of organisations that participate actively in the PPP;
  • Significant involvement of SMEs and web entrepreneurs to the PPP;
  • Constant increase in the number of data professionals in different sectors, domains and various operational functions within businesses;
  • Networking of national centres of excellence and the industry, contributing to industrially valid training programs.

b. Research and Innovation actions

  • Availability of solid, relevant, consistent and comparable metrics for measuring progress in Big Data processing and analytics performance;
  • Availability of metrics for measuring the quality, diversity and value of data assets;
  • Sustainable and globally supported and recognized Big Data benchmarks of industrial significance.

SpecificChallenge:

The newly created Big Data Value contractual public-private partnership (cPPP) needs strong operational support for community outreach, coordination and consolidation, as well as widely recognised benchmarks and performance evaluation schemes to avoid fragmentation or overlaps, and to allow measuring progress in (Big) Data challenges by solid methodology, especially in emerging areas where the significance of Big Data is rapidly increasing. Also, there is an urgent need to improve the education, professional training and career dynamics (including addressing the existing gender gaps in ICT) so that the profiles of data professionals better respond to the rapidly evolving needs of data intensive industry sectors.


Scope:

a. One Coordination and Support Action (CSA) will perform all of the following tasks:

  • support the community building, the administration and governance of the cPPP, in close collaboration with the cPPP governance bodies; facilitate discussion on relevant topics such as the framework conditions of the data economy; organise events and contribute to synergies and coordination between the actors and stakeholders of the cPPP and beyond;
  • liaise with and build on related actions[[Such as the European Data Science Academy (<a href="http://edsa-project.eu/">http://edsa-project.eu/</a>), EIT ICT Labs KIC and Marie Sklodowska-Curie Actions (MSCA)]] and support the establishment of national centres of excellence in all Member states, and exchange knowledge on the universities' data scientist programmes across all Member States; to align curricula and training programmes to industry needs; to stimulate and promote (among the organisations participating in the Big Data PPP actions) exchanges of students, confirmed data professionals and domain experts that would acquire data skills and let them work on a specific Big Data challenge/project in a company or a research centre/university in another Member State.

The Commission considers that proposals requesting a contribution from the EU of about EUR 5 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts. No more than one action will be funded.

b. Research and Innovation Actions

The benchmarking action will identify specific data management and analytics technologies of European significance, define benchmarks and organise evaluations that allow following their certifiable progress on performance parameters (including energy efficiency) of industrial significance. The benchmarking and evaluation schemes will liaise closely with data experimentation/integration (ICT-14) and Large Scale Pilot (ICT-15) projects to reach out to key industrial communities, to ensure that benchmarking responds to their real needs and problems, and to provide a basis for measuring the success of the PPP. The "European significance" of industry/technology sectors should be determined and documented by objective criteria such as turnover, world-wide market share and growth rates of the European companies who provide or use such technologies. When real datasets cannot be made available for benchmarking, synthetic datasets will be acceptable, provided that they are produced by models that certifiably produce data distributions approximating real datasets in all respects that are industrially relevant. The action shall address areas of activity that do not yet have a benchmarking/evaluation scheme.

The Commission considers that proposals requesting a contribution from the EU of about EUR 2 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.


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