The Big Data Value Strategic Research and Innovation Agenda Version - - PowerPoint PPT Presentation

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The Big Data Value Strategic Research and Innovation Agenda Version - - PowerPoint PPT Presentation

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The Big Data Value Strategic Research and Innovation Agenda Version 2.0 Prof. Dr. Milan Petkovi , Vice President BDVA, Philips www.bdva.eu 08.07.16 1 Big Data Public Private Partnership European Commission EU and Industry Contractual

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The Big Data Value Strategic Research and Innovation Agenda Version 2.0

  • Prof. Dr. Milan Petković, Vice President BDVA, Philips
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Big Data Public Private Partnership

European Commission

Big Data Projects within Horizon 2020

  • Projects running within 2017

– 2021

  • Expected Total Funding

~ 500 MEUR

Big Data Value AssociaHon

  • Industry driven, Defines

Research and InnovaHon Agenda, Specifies Key Performance Indicators

AssociaHon proposes research objecHves

Grant Agreement per project

EU and Industry agreed on a cPPP to conduct strategic Big Data Value research and innovation

Stakeholder Community

Stakeholders Large Industry SMEs Research community End users

Contractual Arrangement

…

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Who is behind BDVA? Board members

(from: hXp://www.bdva.eu/?q=board-members)

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When is Data ‘Big’ for BDVA? A bet for Value

Volume Velocity Veracity Variety Value Data at Rest

Terabytes to exabytes of exis@ng data to process

Data in Mo@on

Streaming data, requiring mseconds to respond

Data in Many Forms

Structured, unstructured, text, mul@media,…

Data in Doubt

Uncertainty due to data inconsistency & incompleteness, ambigui@es, latency, decep@on

€ € € € € € € €

Data into Money

Business models can be associated to the data

Adapted by a post of Michael Walker on 28 November 2012

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Boost European BIG DATA research, development and innovation by: strengthening competitiveness and ensuring industrial leadership promoting the widest and best uptake of BIG DATA technologies and services establishing the excellence of the science base in the field of BIG DATA

Goals of BDVA

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Work together to organize an IMPACTFUL program Efficiency: Further develop the EU big data ecosystem (i- Spaces) Proof points: Demonstrate the impact of Big Data and show the value (Lighthouses - large scale pilots) Innovation: Create impactful research results

BDVA focus points

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BDVA internal activities

TF1: Programme: Contributing to the H2020 Programme content of the BDV PPP TF2: Impact: Maintain the various KPIs defining the expected Impact of BDV PPP TF3: Community: Big data community engagement and participation TF4: Communication: Communication plan for creating awareness around the BDVA TF5: Legal: Bridge Big Data technology with legal and policy matters TF6: Technical: Identifying and refining the technical challenges of the programme – eg Data Management TF7: Application: Domain usage group which can influence others – eg Telecoms TF8: Business: Examining the business and economic influences and business areas TF9: Societal: Examining the societal impact on business, citizens TF10: Skills and Education: What skills are needed for the next knowledge workers TF0: Administrative and strategic activities requested by BDVA GA/BOD

Organiza@on

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Inclusion

Organiza@on

TF3: Community TF4: CommunicaHon

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Block your agenda: BDVA Summit (29 Nov-2Dec)

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BDVA internal activities

TF1: Programme: Contributing to the H2020 Programme content of the BDV PPP TF2: Impact: Maintain the various KPIs defining the expected Impact of BDV PPP TF3: Community: Big data community engagement and participation TF4: Communication: Communication plan for creating awareness around the BDVA TF5: Legal: Bridge Big Data technology with legal and policy matters TF6: Technical: Identifying and refining the technical challenges of the programme – eg Data Management TF7: Application: Domain usage group which can influence others – eg Telecoms TF8: Business: Examining the business and economic influences and business areas TF9: Societal: Examining the societal impact on business, citizens TF10: Skills and Education: What skills are needed for the next knowledge workers TF0: Administrative and strategic activities requested by BDVA GA/BOD

TF1: Programme TF1.SG4: i-Spaces

TF1.SG4-D1: DescripHon of BDV PPP Instruments: Lighthouse projects and i- Spaces TF1.SG4-D2:Survey of exisHng i-Spaces within Europe and Globally TF1.SG4-D3: IdenHficaHon of CriHcal Success Factors for i-Spaces

Efficiency

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i-Spaces - big data innovation ecosystems

Network/Federation

  • Collaboration
  • Best practices
  • Standardization

Infrastructures for Data Access

  • Hardware
  • Platforms (OSS – Proprietary)
  • Scientific Personal
  • Access and Support for Test/Trials/

Validation Data Sources – Data Access

  • Private & Industrial
  • Open Data
  • Secure / Confidential Environment

Skills / Training

  • Tools /Methods
  • Data scientists = IT & Domain
  • Interdisciplinary

Data integration challenges

  • Many formats
  • Different quality

Bring Data Owners and Data Innovators together Efficiency

  • In secure, precompeHHve, controlled

environment

  • From „proof of concept“ to „proof of ROI“ to

create value

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I-Spaces will deliver:

Improve Data Availability for Innovation

  • Controlled access to industrial and private data assets

Support Cross-Domain Data Integration

  • Simplify data analytics carried out over datasets from

different companies and sectors

  • Shorten time to market for new products and services

across sectors Incubate and Support Data Experimentation

  • Participation of SMEs and web entrepreneurs
  • Support testing and benchmarking of technologies,

applications, and business models.

Efficiency

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BDVA internal activities

TF1: Programme: Contributing to the H2020 Programme content of the BDV PPP TF2: Impact: Maintain the various KPIs defining the expected Impact of BDV PPP TF3: Community: Big data community engagement and participation TF4: Communication: Communication plan for creating awareness around the BDVA TF5: Legal: Bridge Big Data technology with legal and policy matters TF6: Technical: Identifying and refining the technical challenges of the programme – eg Data Management TF7: Application: Domain usage group which can influence others – eg Telecoms TF8: Business: Examining the business and economic influences and business areas TF9: Societal: Examining the societal impact on business, citizens TF10: Skills and Education: What skills are needed for the next knowledge workers TF0: Administrative and strategic activities requested by BDVA GA/BOD

TF7: ApplicaHons TF7.SG1: Emerging applica@on domains TF7.SG2: Telecom TF7.SG3: Healthcare TF7.SG4: Geo/space

Proof points

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Lighthouses: Adoption of big data by industrial sectors

Proof points

Integrate the European Open Data Portal as Data Provider in a new Ecosystem.

US$3.24 trillion spent on Healthcare in the US in 2015 Europe spends about 10% of its GDP on Healthcare Volume of healthcare data: 153 exabytes in 2013 to 2314 exabytes by 2020 European Health insurance market worth €119bn in 2014

  • Demonstrate Big Data Value in a

target industrial sector

  • Large-scale data-driven

demonstraHons

  • Propose replicable solu@ons by

using exisHng technologies or very near to market technologies

  • Create high level impact and

broadcast visibility

Demonstrate increase of produc@vity/compe@@veness of the target sector

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BDVA internal activities

TF1: Programme: Contributing to the H2020 Programme content of the BDV PPP TF2: Impact: Maintain the various KPIs defining the expected Impact of BDV PPP TF3: Community: Big data community engagement and participation TF4: Communication: Communication plan for creating awareness around the BDVA TF5: Legal: Bridge Big Data technology with legal and policy matters TF6: Technical: Identifying and refining the technical challenges of the programme – eg Data Management TF7: Application: Domain usage group which can influence others – eg Telecoms TF8: Business: Examining the business and economic influences and business areas TF9: Societal: Examining the societal impact on business, citizens TF10: Skills and Education: What skills are needed for the next knowledge workers TF0: Administrative and strategic activities requested by BDVA GA/BOD

Innova@on

TF6: Technical TF1: Programme

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BDV SRIA Technical Priorities

Deliver new Big Data technology allowing for deep analytics capacities on data- at-rest and data-in-motion while providing sufficient privacy guarantees, optimized user experience support and a sound data engineering framework.

Data Management Data Processing Architectures Data Analytics Data Protection Data Visualization and User Experience

Innova@on

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The Big Data Value Strategic Research and Innovation Agenda (BDV SRIA) defines the

  • verall goals, main technical and non-technical

priorities, and a research and innovation roadmap for the European contractual Public Private Partnership (cPPP) on Big Data Value.

SRIA Update – Community Survey - 2016

Strategic Research and Innovation Agenda

What is the SRIA?

  • Built upon inputs and analysis from SMEs and Large

Enterprises, public organisaHons, and research and academic insHtuHons.

  • Mul@ple workshops and consulta@ons took place to ensure

the widest representaHon of views and posiHons

  • Approximately 200 organisa@ons and other relevant

stakeholders physically par@cipa@ng and contribuHng.

SRIA is based on strong community involvement

We invite you to share your opinion by answering a short quesHonnaire on hXp://www.bdva.eu Open un@l 30. September 2016.

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2016 2017 2018 2019 2020

Horizon 2020 Work Programme 16/17 18/ 19 2020 Beyond PPP

Lighthouse Projects European InnovaHon Spaces R&I and InnovaHon Projects Ecosystem Enablers

Three Stage Programme

1st Gen. High-Impact Sectors 2nd Gen. High-Impact Sectors Establish Federation Governance Innovation Acceleration

Phase 1 Establish InnovaHon Ecosystem Phase 2 Pioneer DisrupHve SoluHons Phase 3 Ecosystem Sustainability

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Examples of LT Challenges in BDVA SRIA

Multilingualism of data sources (get the data) Tools are generally provided for English Semantic interoperability (get the meaning) Semantic annotation of unstructured and semi- structured data Standards and multilingual knowledge repositories/ sources Technical challenges in NLP, information extraction, machine learning, linked-data… “The different languages within Europe create a barrier (multilingualism) during data processing”

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THANK YOU

Further Information: Milan Petkovic: milan.petkovic@philips.com (Vice President BDVA) Edward Curry: edward.curry@insight-centre.org (Vice President BDVA) BDVA: http://www.bdva.eu/ info@bigdatavalue.eu