Big Data challenges to foster AI research and applications

GRUPPO TELECOM ITALIA
Workshop on Embracing Potential of Big Data
Pisa, 12 Dicembre 2014
Big Data challenges to foster AI research
and applications
Fabrizio Antonelli – SKIL Lab
The Joint Open Labs of Telecom Italia
Joint Open Labs are research and innovation laboratories set up within university centres, as a
result of partnerships and agreements between Telecom Italia and the major Italian universities
in specific fields of scientific and technological interest.
JOLs in brief:
 5 universities involved in the first phase (Polytechnic University of
Turin, Polytechnic University of Milan, Trento University, Sant’Anna
School of Advanced Studies in Pisa and Catania University)
 Interdisciplinary teams focusing on university areas of excellence
 "Open” research at international level in collaboration with
organisations such as the European Institute of Technology (EIT) and
Massachusetts Institute of Technology (MIT)
8 JOLs
within 5 Italian
universities of
excellence
13 million
euros
invested
(2012 to
2015)
350 young
people (200
in the
innovation
area)
25%
PhDs
funded
within JOLs
15%
thesis /
internships
Big Data challenges to foster AI research and applications
Fabrizio Antonelli, SKIL Lab 2
Joint Open Labs throughout Italy
Robotics
Semantics & Big Data
Mobile Smart Spaces
Internet of Things
TO
TN
MI
E-Health and Wellbeing
Multimedia
PI
Mobile Social Platforms
Mobile devices Lab
Big Data challenges to foster AI research and applications
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Challenges around the World
21st Century Grand Challenges
http://www.whitehouse.gov/administration/eop/ostp/grand-challenges
Big Data challenges to foster AI research and applications
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Challenges around the World
Orange D4D Challenge
http://www.d4d.orange.com/en/home
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Challenges around the World
Censimenti Data Challenge
http://censimentoindustriaeservizi.istat.it/istatcens/censimenti-data-challenge-il-contest-sui-dati-del-censimento/
Big Data challenges to foster AI research and applications
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Challenges around the World
Piemonte Visual Contest
http://www.piemontevisualcontest.eu
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Motivations
Big Data
Big solutions?
Big Data challenges to foster AI research and applications
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Motivations
Lack of finding specific
competences
The web as the enabler to
put in touch demand and
offer
Increasing will of
participation
Need of engaging
the ecosystem
Big Data challenges to foster AI research and applications
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The cultural change
What prevents from a broader adoption of the challenges as a new paradigm of innovation
•
•
Trust in external developers not engaged with traditional
processes
Open up their data, IP, asset (the attendees get enough
information that they can create relevant solution for these
corporate)
•
Regulatory framework constraints
•
Internal frictions
•
Developing a strategy
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www.telecomitalia.com/bigdatachallenge
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The Telecom Italia Big Data Challenge 2014
Telecom Italia BIG DATA CHALLENGE is an initiative aimed
at involving researchers, developers and designers from
all the globe on the Big Data.
The CHALLENGE gives the chance to connect with an
international network of professionals for collecting ideas
and approaches on heterogeneous Big Data exploitation
(private data, open data, sensor data, etc.) through the
development of APPLICATION, ANALYTICS and
VISUALIZATION.
Big Data challenges to foster AI research and applications
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In collaboration with
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How was it designed?
Telecom Italia BIG DATA CHALLENGE was divided in two
phases:
A first phase (2 months long) where individuals or teams can apply for
participation and download a DATASET of heterogeneous data
(Telecommunication, transportation, weather, etc.) referred to a
specific period to be used for the development of apps, analytics or
visualizations.
A second phase (Big Data Jam), during the ICT DAYS 2014 in Trento*,
where in a 2 days of meetings, panels and workshops the participants
are invited to present their work and where a committee (made of
personalities from the scientific, institutional and industrial world) will
reward the best ideas.
* 2013.ictdays.it/it
Big Data challenges to foster AI research and applications
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How was it structured?
Telecom Italia BIG DATA CHALLENGE was structured in
TRACKS. Each participant can apply for a specific track
according to her competence or interest.
The available TRACKS are:
1.
2.
3.
APP DEVELOPMENT: development of data-oriented application
starting from the available data
DATA ANALYTICS: data mining for the extraction of correlations,
patterns, trends, etc.
DATA VISUALIZATION: development of visualizations for the data
storytelling.
Big Data challenges to foster AI research and applications
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What kind of data?
The participants can download a geo-referred DATASET
(period of Nov/Dec 2013) related to two different Italian
territories made of several millions records:
The TRENTINO region and the METROPOLITAN AREA OF
MILAN
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What kind of data?
Big Data challenges to foster AI research and applications
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What kind of data?
Big Data challenges to foster AI research and applications
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The Dandelion data distribution platform (powered by SpazioDati)
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Prizes
•
6000€ for the first selected idea in any of the 3 tracks
Other benefits:
•
•
Exhibition of the visualizations in the MUSE museum and
in other EIT ICT Labs nodes
Special Issue on EPJ Data Science Journal, edited by
Frank Schweitzer (ETH Zurich) and Alessandro
Vespignani (Northeastern University)
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Numbers
Participants: 1108
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Numbers
100+ submissions
10 finalists
3 winners
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Winning team – APP DEVELOPMENT
Project: Living Land Use - Team: LocaliData
Idea – analyse the activity data to elicit land use footprints
The Living Land Use application aims at:
1. Deriving land use "footprints" of
Milano by analysing the "activity data"
provided by the Big Data Challenge
2013
2. Comparing the "elicited" land use
footprints with the land use
classification provided by CORINE in
2009
3. Identifying relevant deviations in land
use between 2009 and 2013
Living Land Use http://livinglanduse.cefriel.com
2013
Milano grid and in-calls footprint for
week days/weekend in cell 6060
Construction site
2009
CORINE land use classification (viz: QGIS, background map: OpenStreetMap)
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Winning team – DATA VISUALIZATION
Project: Human impact from a bird’s eye view - Team: Easystats Ltd
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Winning team – DATA ANALYTICS
Project: People as Sensors for Predicting Energy Consumption - Team: University of Trento
The goal is to optimize electric energy producer-distributor-consumer value
chain in Trentino province (Italy).
●
●
Predict average daily energy consumption for each line through the
electrical grid of the Trentino province (Italy) based on human behavioral data,
derived from mobile phone aggregated and anonymized activity, => thus
optimizing the economy of energy producers and distributors value chain and
reducing climate change impact.
Predict peak daily energy consumption for each line through the electrical
grid of the Trentino province (Italy) based on human behavioral data, derived
from mobile phone aggregated and anonymized activity, => thus meeting
consumer peak demand.
Big Data challenges to foster AI research and applications
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What’s next
The Telecom Italia Big Data Challenge have now been released in
open source
http://theodi.fbk.eu/openbigdata/
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What’s next
We’ll see you at
Telecom Italia Big Data
Challenge 2015!
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Grazie
Thanks
[email protected]
@faberAntonelli