In this video from the ISC Big Data'14 Conference, Edward Curry from the NUI Galway & Nuria de Lama Sanchez from Atos present: New Horizons for a Data-Driven Economy – A Roadmap for Big Data in Europe. "In this talk we summarize the results of the BIG project including analysis of foundational Big Data research technologies, technology and strategy roadmaps to enable business to understand the potential of Big Data technologies across different sectors, together with the necessary collaboration and dissemination infrastructure to link technology suppliers, integrators and leading user organizations." Learn more: http://www.isc-events.com/bigdata14/schedule.html and http://big-project.eu/ Watch the video presentation: http://wp.me/p3RLEV-37G

1. ISC BIG DATA – October 2nd, 2014 - Heidelberg
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Big Data Public Private Forum
THE BIG PROJECT: RESULTS AND IMPACT
October 2nd, Heidelberg
Edward Curry, Insight @ NUI Galway
Nuria de Lama, Representative of Atos Research & Innovation to the EC

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BIG DATA: EUROPE NEEDS TO REACT!
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Big Data is mainstream in North America, but Europe lagged behind due to
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Size factor: smaller organizations and smaller data sets
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Expensive, scarce data analytics skills
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Economic crisis, cautiousness in new investments

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BIG DATA IN EUROPE
“Possibly one of the few last chances for Europe‘s software industry to take a true leadership “ K-H Streibich, CEO
“This is a revolution: and I want the EU to be right at the front of it.” Neelie Kroes, Vice-President of the European Commission responsible for the Digital Agenda, March 2013

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The BIG Project
BIG aims to promote a well-developed EU industrial landscape in Big Data:
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Providing a clear picture of existing technology trends and their maturity
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Acquiring a sharp understanding of how Big Data can be applied to concrete environments / use cases
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Pushing European Big Data research and innovation to contribute to European competitiveness (“define how the future should look like”)
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Building a self-sustainable, industry-led initiative (implementation)
Overall Objective
Work at technical, business and policy levels, shaping the future through the positioning of IIM and Big Data specifically in Horizon 2020.
Bringing the necessary stakeholders into a self-sustainable industry-led initiative, which will greatly contribute to enhance the EU competitiveness taking full advantage of Big Data technologies.

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A PAN-EUROPEAN EFFORT
Funding: Euros 2.499.998,00 Duration: 26 months

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BIG - THREE LEVEL APPROACH
Big Data Public Private Partnership
Impact Assessment
Sustainability
Towards Horizon 2020
Roadmapping activity
Individual roadmap elaboration (per sector)
Roadmap consolidation (cross-sectorial)
Technology state of the art and sector analysis
Definition of the proposed application sectors
Asses the impact/applicability of the different technologies
Big Data Initiative definition

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HOW: SECTORIAL FORUMS AND TECHNICAL WORKING GROUPS
Health
Public Sector
Finance & Insurance
Telco, Media& Entertainment
Manufacturing, Retail, Energy, Transport
Needs
Offerings
Big Data Value Chain
Technical Working Groups
Industry Driven Sectorial Forums
Data
Acquisition
Data
Analysis
Data
Curation
Data
Storage
Data
Usage
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Structured data
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Unstructured data
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Event processing
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Sensor networks
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Protocols
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Real-time
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Data streams
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Multimodality
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Stream mining
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Semantic analysis
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Machine learning
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Information extraction
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Linked Data
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Data discovery
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‘Whole world’ semantics
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Ecosystems
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Community data analysis
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Cross-sectorial data analysis
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Data Quality
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Trust / Provenance
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Annotation
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Data validation
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Human-Data Interaction
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Top-down/Bottom-up
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Community / Crowd
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Human Computation
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Curation at scale
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Incentivisation
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Automation
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Interoperability
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In-Memory DBs
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NoSQL DBs
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NewSQL DBs
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Cloud storage
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Query Interfaces
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Scalability and Performance
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Data Models
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Consistency, Availability, Partition- tolerance
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Security and Privacy
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Standardization
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Decision support
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Prediction
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In-use analytics
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Simulation
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Exploration
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Visualisation
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Modeling
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Control
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Domain-specific usage

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RELEVANT SOURCES: SUBJECT MATTER EXPERT INTERVIEWS

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AVAILABILITY OF A WIDE SPECTRUM OF RESULTS
Interviews, Technical White Papers, Sector's requisites and Roadmaps available on: http://www.big-project.eu
Expert Interviews
Technical Whitepapers
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Executive Overview
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Key Insights
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Social & Economic Impact
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Concise State of the Art
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Future Requirements & Emerging Trends
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Sector-specific Case Studies

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THE DATA LANDSCAPE
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Big Data technology is mostly evolutionary
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Old technologies applied in a new context
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Volume, Variety, Velocity, Value …
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Business processes change must be revolutionary to enable new opportunities
Technology Evolution
Process Revolution
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The long tail of data variety is a major shift in the data landscape
Variety
Reuse
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Cross-sectorial uses of Big Data will open up new business opportunities

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BIGGEST BLOCKERS
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Lack of Business-driven Big Data strategies
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Undiscovered & unclaimed business values
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Data Sharing & Exchange
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Need for format and technology standards
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Data Privacy and Security
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Regulations & markets for data access
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Legal frameworks for data sharing & communication are needed
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Human resources
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Lack of skilled data scientists and data engineers
Key Technical Requirements

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COMMON REQUIREMENTS
Data Privacy and Security
Legal frameowrks for data sharing & communication are needed
Investment Long-term investments require conjoint engagement of several partners
Not-Technology-related
Data Digitalization only small percentage of data is documented (lack of time) with low quality
Data Enrichment transform unstructured data into structured format
Data Sharing & Integration Overcome data silos and inflexible interfaces
Business Cases Undiscovered und unclaimed potential business values
Regulation & Technology
Technology-related
Data Quality Reliable insights for health-related decisions require high data quality
Openness
Leadership to promote common standards for Open Data: APIs, format and schemas, as well as covering licensing and legal aspects
Data ownership
Fragmentation of data ownership that leads to the data silo and interoperability issues

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SECTORIAL ROADMAPS
Health
Public Sector
Finance & Insurance
Telco, Media& Entertainment
Manufacturing, Retail, Energy, Transport

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PUBLIC PRIVATE PARTNERSHIP

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MOTIVATION
Needs for everyone to remain competitive
Opportunities for only a few?

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Europe has to react! ……A Call for Action
“a public private partnership…can be a powerful way to work together…Public money is not free money. Before you can unlock it you need a very clear plan, showing how any public investment will work, how it connects to the activities around it, and how it will pay off…we need a Strategic Research and Innovation Agenda … from a broad, inclusive and representative basis, pulling together different priorities, so they make sense……… we need to do all this quickly, and to the highest quality”
Neelie Kroes
Vice-President of the European Commission

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DRIVERS
NESSI Partners
NESSI Membership
> 450 members
http://www.nessi-europe.eu/
http://www.big-project.eu/
http://www.bigdatavalue.eu/

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THE BIG DATA VALUE PPP (PUBLIC-PRIVATE PARTNERSHIP)
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The goal of the Big Data Public Private partnership is to increase the amount of productive European economic activities and the number of European jobs that depend on the availability of high quality data assets and the technologies needed to derive value from them.
European cross-organizational and cross-sector environments
Meeting point for different stakeholders (small, big companies, academia…supply & demand) to discover economic opportunities based on data integration and analysis
Resources to develop working prototypes to test the viability of actual business development
Availablity of data assets (secure environments to enhance data sharing; i.e. not only open data)
Technologies to derive value from them (this could entail bringing analytics close to data)

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MUTIDISCIPLINARITY

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I-SPACES: THE RELEVANCE OF THE ECOSYSTEM
Technology
A true open innovation ecosystem

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BUILDING UPON EXISTING INFRASTRUCTURES AND TECHNOLOGIES: DATA INCUBATORS
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TeraLab (FR): digital services platform that provides both the research community and businesses, with an environment conducive to research and experimentation focused on innovative applications and industrial prototypes in the field of Big Data
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Physical resources (including a substantial processing capacity with several teraoctets of RAM), huge databases and various cutting-edge applications and tools (through SAAS/PAAS model)
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Facilitating batch or real-time processing and storage of huge amounts of data
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Data assets: anonymous, publicly-available information (e.g. OpenStreetMap, Common Crawl), and open data, but also data which has been processed to render it anonymous, provided by professional sources
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Access via secure and ultra-secure systems using technology provided by the CASD (Centre for Secure Remote Access).
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SDIL (DE): Similar approach in the domains of
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Industry 4.0
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Energy
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Smart Cities
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Health

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RESEARCH PRIORITIES
Privacy and anonymisation mechanisms
Improving understanding of data by deep analytics (e.g. predictive modelling, graph mining, ...)
Optimized Architectures for analysing data including real-time data
(e.g.recommendation engines, ...)
Visualization and user experience
(e.g. User adaptive systems, search capabilities, ...)
Data management engineering (e.g. Data integration, data integrity, ...)
Innovation Spaces serve as hubs for bringing the technology and application developments together and cater for the development of skills, competence, and best practices.
Lighthouse Projects Large scale demonstrations focusing on certain sectors and domains
Research Priorities
Instruments

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ESTIMATED EXPECTED R&D OUTCOMES
Year 1
Year 2
Year 3
Year 4
Year 5
Priority : privacy and anonymisation
Generalisation of Secure Remote Data Access Centre techniques.
Method for deletion of data and data minimization.
Robust anonymisation algorithms
Priority : deep analysis
Improved statistical models by enabling fast non-linear approximations in very large datasets
Predictive modeling
Graph mining techniques applied on extremely large graphs
Real-time analytics
Semantic analysis in near-real-time
Algorithms for multimedia data mining
Deep learning techniques
Descriptive language for deep analytics.
Contextualisation.
Priority : architectures for analytics of data at rest and in motion
Optimized tools for the integration of existing components to new types of platforms with both data at rest and in motion.
Synergies between massively parallel architectures (MPP) and batch processing/stream processing architectures
Priority : advance visualisation
New data search solutions / paradigms
Semantic driven data visualisation – stronger links between visualization and analytics
User adaptation
Collaborative real- time, dynamic 3D solutions
Priority : engineering data management
APIs for improving the process of data transformation
Collaborative Tools and techniques for Data Quality (including integrity and veracity check)
Harmonized description format for meta-data
Methodology, models and tools for data lifecycle management
Data management as a service

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BIG DATA CHALLENGES EXPAND TECHNOLOGY
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Privacy & Regulation
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Incentives and awareness to foster adoption
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Traditional industries
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New industries
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Business models and commercialization
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Skills

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PROCESS & TIMING
Launch of the BDV PPP
Investment of approximately €1068M for [2016-2020]

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STAKEHOLDER INVOLVEMENT
Big Data Strategies of User Industry, Source: Morgan Stanley

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VALUE PROPOSITION
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Technology and data assets development
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Means for benchmarking and testing
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performance of some core technologies (querying, indexing, feature extraction, predictive analytics, visualization…)
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business applications evaluated according to different criteria (ex. usability)
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Development of business models
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Optimizing existing industries
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New business models along new value chains
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Improvement of the skills of data scientists and domain practitioners (enrich educational offering)
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Dissemination of best practices  showcases to stimulate big data adoption and transfer of solutions across sectors
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Analysis of societal impact  transfer of data management practices to domains of societal interest (health, environment…)

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FORMAL SIGNING EVENT OF THE PPP Date: 13th October 2014 Place: Brussels Contact:
CNECT-G3-EVENTS@ec.europa.eu, mentioning "Event for the Big Data PPP Signature" in the subject field