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.

1. Edward Curry, National University of Ireland Galway
European Data Forum, Athens, 20 February 2014

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. 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

5. 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

6. 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

7. 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
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