Download Data Methods - Indico

Pasquale Pagano
ISTI – CNR (Italy)
[email protected]
RICH session at the EGI Community Forum 2015
Social Mining & Big Data Analytics
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A TOOL TO
MEASURE,
UNDERSTAND,
AND POSSIBLY
PREDICT
HUMAN BEHAVIOR
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Outline
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Consortium
Goals
Stakeholders
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Consortium
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1 - CNR Consiglio Nazionale delle Ricerche Italy
2 - USFD The University of Sheffield UK
3 - UNIPI Università di Pisa Italy
4 - FRH Fraunhofer IAIS and IGD Germany
5 - UT Tartu Ulikool Estonia
6 - IMT Scuola IMT Lucca Italy
7 - LUH Gottfried Wilhelm Leibniz Universitaet
Hannover Germany
8 - KCL King’s College London UK
9 - SNS Scuola Normale Superiore di Pisa Italy
10 - AALTO Aalto University Finland
11 - ETHZ ETH Zurich Switzerland
12 - TUDelft Technische Universiteit Delft Netherlands
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
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Goals
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Goal #1
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Integrating key national infrastructures and centres
of excellence at European level in big data analytics
and social mining
to create a networked virtual ecosystem
the SoBigData RI.
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
National Ris to be integrated
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SoBigData.it CNR & University of Pisa & SNS & IMT
www.sobigdata.it
GATE USFD, Sheffield UK http://gate.ac.uk
IVAS Fraunhofer IGD, Darmstadt, DE
https://www.igd.fraunhofer.
Alexandria LUH, Hannover, DE http://www.L3S.de
Aalto Helsinki, Finland
E-GovData Tartu, Estonia http://www.cs.ut.ee
Living Archive, Zurich, Switzerland
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Goal #2
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SoBigData leveraging these rich scientific assets (big
data, analytical tools and services, and skills),
will enable cutting-edge, multi-disciplinary social
mining experiments
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
SoBigData.eu thematic clusters
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Six thematic clusters of competences and services
 Text
and Social Media Mining
 Social Network Analysis
 Human Mobility Analytics
 Web Analytics
 Visual Analytics
 Social Data
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Reference scenarios
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Big Data for well-being indicators: Diversity and
Well-being (Statistics 2.0)
Big Data for understanding human mobility (Smart
communities & smart cities)
Big Data for Epidemic Forecasting: epidemiology
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Goal #3
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Granting access (both virtual and trans-national onsite) to the SoBigData RI to multidisciplinary scientists,
innovators, public bodies, citizen organizations, SMEs,
as well as data science students at any level of
education.
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
SoBigData.eu Access
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Two access modalities to data and methods:

Transnational Access
 Exploratory
Projects
 Blue-sky projects

Virtual Access
 Data
and Methods Catalogue(s)
 Modular virtual research environment
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
SoBigData.eu Virtual Access
[1]
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Data



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

Methods
Publication and
validation
Policy definition
Anonymization
Encryption
Embargo definition
Accounting monitoring
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



Publication and
validation
Policy definition
Linking to data
Contextualization
Provisioning
Accounting monitoring
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
SoBigData.eu Virtual Access
[2]
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Data and Methods entities will become infrastructure resources
Entity
As a resource
•
•
•
•
•
• Methods
• Data





Publication
Lifecycle mgmt.
Failure mgmt.
Authorization
Accounting
Data
Publication and
validation
Policy definition
Anonymization
Encryption
As a service



Embargo
definition
Accounting
monitoring

• Access
• Orchestrate
• Reference
Methods
Publication and
validation

Policy definition

Linking to data

Contextualization


SoBigData: Social Mining and Big Data Ecosystem
Provisioning
Accounting
monitoring
11/11/15
SoBigData.eu Virtual Access
[3]
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Data and Methods defined through the Platform
 Will be
registered in the Catalogue(s)
 made exploitable via VREs



created dynamically

to include subset of resources (data, methods)

according to the defined policies

to serve the needs of subset of users for a defined timeframe
operated by the D4Science infrastructure as service
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
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Stakeholders
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Stakeholders
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Big data analysts and social informatics
researchers
• to enhance their algorithms by dealing with multi-disciplinary
social data for the future digital economy and society
Economists, social science and humanities
researchers, journalists, policy and law makers
• to analyse the avalanche of (big) social data, in order to
gain insight and actionable knowledge
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Stakeholders
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Researchers in related communities
• to use the algorithms, the analytical competences and
the data infrastructure
Industrial innovators & startuppers
• to create rapid proof-of-concepts of data-driven
innovative ideas and services
The public as a whole
• to understand their role in the production, consumption
and value-creating of social data
SoBigData: Social Mining and Big Data Ecosystem
11/11/15
Thank You
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Contact Points
 Project Steering Board

Fosca Giannotti


Kalina Bontcheva


[email protected]
Dino Pedreschi


[email protected]
[email protected]
Valerio Grossi

[email protected]
SoBigData: Social Mining and Big Data Ecosystem
11/11/15