Edward Curry, National University of Ireland Galway
European Data Forum, Athens, 20 February 2014
SECTORIAL FORUMS AND TECHNICAL
WORKING GROUPS
Health Public Sector
Finance &
Insurance
Telco, Media&
Entertainment
Manufac...
Senior
Academic
Senior
Management
Middle
Researcher
Middle
Management
Position in Organisation
University
MNC
SME
Other
Ty...
Interviews and Technical White Papers available on:
http://www.big-project.eu
Expert Interviews Technical
Whitepapers
▶ Ex...
Key Trends
▶ Lower usability barrier for data tools
▶ Blended human and algorithmic data processing for coping with
for da...
Data
Acquisition
Data
Analysis
Data
Curation
Data
Storage
Data
Usage
Axel Ngonga
ngonga@infor
matik.uni-
leipzig.de
John D...
EDF2014: BIG - NESSI Networking Session: Edward Curry, National University of Ireland Galway: The Big Data Value Chain
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EDF2014: BIG - NESSI Networking Session: Edward Curry, National University of Ireland Galway: The Big Data Value Chain

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BIG - NESSI Networking Session, Talk by Edward Curry, National University of Ireland Galway at the European Data Forum 2014, 20 March 2014 in Athens, Greece: The Big Data Value Chain.

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EDF2014: BIG - NESSI Networking Session: Edward Curry, National University of Ireland Galway: The Big Data Value Chain

  1. 1. Edward Curry, National University of Ireland Galway European Data Forum, Athens, 20 February 2014
  2. 2. SECTORIAL FORUMS AND TECHNICAL WORKING GROUPS Health Public Sector Finance & Insurance Telco, Media& Entertainment Manufacturing, Retail, Energy, T ransport Needs Offerings Big Data Value Chain Technical Working Groups Industry Driven Sectorial Forums Data Acquisition Data Analysis Data Curation Data Storage Data Usage • Structured data • Unstructured data • Event processing • Sensor networks • Protocols • Real-time • Data streams • Multimodality • Stream mining • Semantic analysis • Machine learning • Information extraction • Linked Data • Data discovery • ‘Whole world’ semantics • Ecosystems • Community data analysis • Cross-sectorial data analysis • Data Quality • Trust / Provenance • Annotation • Data validation • Human-Data Interaction • Top-down/Bottom-up • Community / Crowd • Human Computation • Curation at scale • Incentivisation • Automation • Interoperability • In-Memory DBs • NoSQL DBs • NewSQL DBs • Cloud storage • Query Interfaces • Scalability and Performance • Data Models • Consistency, Availabil ity, Partition- tolerance • Security and Privacy • Standardization • Decision support • Prediction • In-use analytics • Simulation • Exploration • Visualisation • Modeling • Control • Domain-specific usage
  3. 3. Senior Academic Senior Management Middle Researcher Middle Management Position in Organisation University MNC SME Other Types of Organisations 1. Literature & Technical Survey 2. Subject Matter Expert Interviews 3. Stakeholder Workshops 4. Online Questionnaire (with NESSI) • Early adopters • Business enablement • Technical maturity • Key Opinion Leaders Methodology Interviewee Breakdown Target Interviewee
  4. 4. Interviews and Technical White Papers available on: http://www.big-project.eu Expert Interviews Technical Whitepapers ▶ Executive Overview ▶ Key Insights ▶ Social & Economic Impact ▶ Concise State of the Art ▶ Future Requirements & Emerging Trends ▶ Sector-specific Case Studies Next versions released in April
  5. 5. Key Trends ▶ Lower usability barrier for data tools ▶ Blended human and algorithmic data processing for coping with for data quality ▶ Leveraging large communities (crowds) ▶ Need for semantic standardized data representation ▶ Significant increase in use of new data models (i.e. graph) (expressivity and flexibility) ▶ Much of (Big Data) technology is evolving evolutionary ▶ But business processes change must be revolutionary ▶ Data variety and verifiability are key opportunities ▶ Long tail of data variety is a major shift in the data landscape The Data Landscape ▶ Lack of Business-driven Big Data strategies ▶ Need for format and data storage technology standards ▶ Data exchange between companies, institutions, individ uals, etc. ▶ Regulations & markets for data access ▶ Human resources: Lack of skilled data scientists Biggest Blockers Technical White Papers available on: http://www.big-project.eu
  6. 6. Data Acquisition Data Analysis Data Curation Data Storage Data Usage Axel Ngonga ngonga@infor matik.uni- leipzig.de John Domingue john.domingue @open.ac.uk Edward Curry ed.curry@der i.org Martin Strohbach MStrohbach@agti nternational.com Tilman Becker becker@dfki.de ▶Join the bigdatavalue.eu mailing list @BIG_FP7 http://big-project.eu/ info@big-project.eu

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