Kimmo Rossi. European Commission DG CONNECT

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1 Kimmo Rossi European Commission DG CONNECT Unit G.3 -Data Value Chain NCP training day, Brussels 18/9/2014

2 What we do Unit CNECT.G3 Data Value Chain FP7/CIP/H2020 project portfolio: Big Data, analytics, language technology Contractual Public-Private Partnership (cppp) on Big Data (being launched) European Data value chain strategy (see: Communication "Towards a thriving data economy") Public Sector Information (PSI) directive, Open Data Portal

technology Contractual Public-Private Partnership (cppp) on Big Data (being

3 Definitions What is Big Data? Very difficult to define (precisely) data is "big" if it defies traditional processing & storage paradigms bigness becomes part of the problem the "3Vs": volume (size), velocity (bytes/s), variety (database, jpeg, video, numbers, text in language X...)...to which we add the 4 th V to denote creation of Value (by linking, aggregating, analysing, visualizing...)

paradigms bigness becomes part of the problem the "3Vs": volume (size), velocity (bytes/s),

4 European Data value chain strategy Objective: to put in place the "systemic" prerequisites for effective use, exchange, re-use, trading... of data assets capacities and skills: build and multiply the "new" competences, prize/recognition schemes infrastructures: Open Data Portal, language resource infrastructure, evaluation platforms, incubators legal and regulatory framework: PSI directive (Public Open Data), data protection and privacy, copyright technology, tools, methods: supporting the above pilots, demonstrators: demonstrating the above in real-world problem settings, market validation

language resource infrastructure, evaluation platforms, incubators legal and regulatory framework: PSI directive (Public Open Data), data protection

5 H2020 Work Programme Our H2020 topics: Big Data & Open data - Innovation ICT15 Big Data Research ICT16 Cracking the language barrier ICT17 Multimodal & natural interaction ICT22a 5

6 ICT 16: In a nutshell Fundamental research in Big Data technologies, addressing analytics (i.e. data mining, machine learning, language understanding, visualization, scalability, responsiveness). User-defined and industry-validated challenges. a) Research and Innovation Actions (RIA) 36 M - Big Data technologies - Benchmarks b) Support Actions (CSA) 1 M - Challenges & competitions in the area of prediction and deep analysis

tal research in Big Data technologies, addressing analytics (i.e. data mining, machine learning, language understanding, visualization, scalability, responsiveness).

7 a) Research and Innovation actions 1. Big Data Research and Innovation Assessing and improving the quality of Big Data Methods, architectures, data structures for Big Data Better Big Data analytics Big Data Prediction, visualization Multilingual/multimodal/diverse Big Data 2. Benchmarks for Big Data analysis and prediction setting up data resources & infrastructure for benchmarking in domains of industrial relevance activity should become self-sustaining by end of project!

structures for Big Data Better Big Data analytics Big Data Prediction, visualization Multilingual/multimodal/diverse

8 Requirements for ICT16.a1 proposals Demonstrate the actual availability of: extremely large and realistically complex European data sets (from the beginning of the action) e.g. European Open data portals, public sector data, Copernicus etc. users/testers for human factors testing, and a serious experimentation methodology

realistically complex European data sets (from the begi

9 b) Challenges and Prize schemes Support actions to define challenges and prize schemes for verifiable performance in tasks requiring extremely large scale prediction and deep analysis. Compact consortia are required to organise and run well-publicised fast turn-around prediction competitions based on European datasets of a significant size. Proposals in this category are expected to be short in duration and are not required to provide sustainability strategies past the end of the project.

Compact consortia are required to organise and run well-publicised fast turn-around prediction competitions based on

10 b) Challenges and Prize schemes Main tasks of the Support Action: Set up, document and promote the challenges Run competitions, award and pay out prizes Administer the prize scheme in compliance with H2020 rules (e.g. Financial Regulation, article 15 of H2020 Annotated Grant Agreement)

out prizes Administer the prize scheme in compliance with H2020 rules

11 New approach: user/industry-defined challenges in FP7: first researchers apply a novel approach that they believe in then they look for use cases/topic/application that would validate their approach in H2020: first industry identifies a problem they have and cannot solve with current methods, then they present it as a challenge to researchers to find solutions, then they define expected impact as a measurable outcome then they try the solutions (run rigorous experiments) then they report the measured outcomes (good or bad)

cannot solve with current methods, then they present it as a challenge to researchers to find solutions, then they define expected

12 Next event We will present Big Data (ICT16) at the Proposers' Day in Florence 9-10 Oct

Florence 9-10 Oct 2014 http://ec.europa.

Kimmo Rossi. European Commission DG CONNECT

Kimmo Rossi. European Commission DG CONNECT Kimmo Rossi European Commission DG CONNECT Unit G.3 - Data Value Chain SC1 info day, Brussels 5/12/2014 1 What we do Unit CNECT.G3 Data Value Chain FP7/CIP/H2020 project portfolio: Big Data, analytics,