edf2014: big - nessi networking session: edward curry, national university of ireland galway: the...
DESCRIPTION
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.TRANSCRIPT
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1European Data Forum 2014 BIG 318062
BIG
Big Data Public Private Forum
The Big Data Value Chain
Edward Curry, National University of Ireland GalwayEuropean Data Forum, Athens, 20 February 2014
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2European Data Forum 2014 BIG 318062
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Sectorial Forums and Technical Working Groups
HealthHealth Public SectorPublic Sector Finance & InsuranceFinance & Insurance
Telco, Media& EntertainmentTelco, Media& Entertainment
Manufacturing, Retail, Energy,
Transport
Manufacturing, Retail, Energy,
Transport
Needs Offerings
Big Data Value Chain
Technical Working Groups
Industry Driven Sectorial Forums
DataAcquisition
DataAnalysis
DataCuration
DataStorage
DataUsage
• Structured data• Unstructured data• Event processing• Sensor networks• Protocols• Real-time• Data streams• Multimodality
• 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
• 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
• 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,
Availability, Partition-tolerance
• Security and Privacy• Standardization
• In-Memory DBs• NoSQL DBs• NewSQL DBs• Cloud storage• Query Interfaces• Scalability and
Performance• Data Models• Consistency,
Availability, Partition-tolerance
• Security and Privacy• Standardization
• Decision support• Prediction• In-use analytics• Simulation• Exploration• Visualisation• Modeling• Control• Domain-specific
usage
• Decision support• Prediction• In-use analytics• Simulation• Exploration• Visualisation• Modeling• Control• Domain-specific
usage
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Technical Workgroup Approach
1. Literature & Technical Survey2. Subject Matter Expert Interviews3. Stakeholder Workshops4. Online Questionnaire (with
NESSI)
• Early adopters• Business enablement• Technical maturity• Key Opinion Leaders
Methodology
Interviewee Breakdown
Target Interviewee
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Subject Matter Expert Interviews
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Working Group results
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
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Key Insights
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, individuals, 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
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Technical Working Group Leaders
DataAcquisition
DataAnalysis
DataCuration
DataStorage
DataUsage
Axel [email protected]
John [email protected]
Edward [email protected]
Martin [email protected]
Tilman [email protected]
▶Join the bigdatavalue.eu mailing list@BIG_FP7
http://big-project.eu/[email protected]