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== Big Data Analytics Expert Group ==
+
= Big Data Analytics Expert Group =
   
  +
== Aim and context ==
 
The objective of this Expert Group is to gather experts on the many faces of Big Data Analytics and compile with their help a white paper that fosters a future agenda for European research on this direction.
 
The objective of this Expert Group is to gather experts on the many faces of Big Data Analytics and compile with their help a white paper that fosters a future agenda for European research on this direction.
 
 
   
 
Sensing big data at a societal scale, and the transparent interlinking of digital and physical reality, has the potential of providing a powerful social microscope, which can help us understand many complex and hidden socio-economic phenomena, such as mobility behaviors, economic and financial crises, the spread of epidemics, the diffusion of opinions and so on. It is clear that such challenge requires high-level analytics, modeling and reasoning across all the social dimensions.
 
Sensing big data at a societal scale, and the transparent interlinking of digital and physical reality, has the potential of providing a powerful social microscope, which can help us understand many complex and hidden socio-economic phenomena, such as mobility behaviors, economic and financial crises, the spread of epidemics, the diffusion of opinions and so on. It is clear that such challenge requires high-level analytics, modeling and reasoning across all the social dimensions.
  +
 
In practice, however, there is a big gap from the opportunities offered by the big data to the challenges posed by social, economical, scientific phenomena: Big data are fragmented and low-level. They reside in diverse databases and repositories, often inaccessible for proprietary and legal constraints, and have limited power to portray different social dimensions. There are many regulatory, business and technological barriers to set the power of big data free.
 
In practice, however, there is a big gap from the opportunities offered by the big data to the challenges posed by social, economical, scientific phenomena: Big data are fragmented and low-level. They reside in diverse databases and repositories, often inaccessible for proprietary and legal constraints, and have limited power to portray different social dimensions. There are many regulatory, business and technological barriers to set the power of big data free.
  +
 
As a response, the paradigm of Big Data Analytics is emerging at the convergence of several disciplines, including machine learning, data mining, statistics, complex systems, socioeconomic sciences, etc. There is a flourishing body of research about making sense of Big Data, but a coherent scientific and technological framework is still missing. We need to put at work scientists and technologists from different disciplines to shape a research and innovation agenda that might drive the ERICM future actions.
 
As a response, the paradigm of Big Data Analytics is emerging at the convergence of several disciplines, including machine learning, data mining, statistics, complex systems, socioeconomic sciences, etc. There is a flourishing body of research about making sense of Big Data, but a coherent scientific and technological framework is still missing. We need to put at work scientists and technologists from different disciplines to shape a research and innovation agenda that might drive the ERICM future actions.
  +
 
We propose here a group that involves prominent research leaders in industry and academia to share their visions and elaborate together what should be the challenging research issues in this promising research frontier.
 
We propose here a group that involves prominent research leaders in industry and academia to share their visions and elaborate together what should be the challenging research issues in this promising research frontier.
   
=== Organization team ===
+
== Organization team ==
   
 
* Fosca Giannotti, ISTI-CNR
 
* Fosca Giannotti, ISTI-CNR
Line 17: Line 19:
 
* Costantino Thanos, ISTI-CNR
 
* Costantino Thanos, ISTI-CNR
   
== Workshop ==
+
== Method of work ==
   
  +
The activity of the Expert Group is planned along three steps:
The workshop of the ERCIM Expert Group on Big Data will take place near Pisa, Italy, '''from May 29th to May 30th, 2014'''. It will be a full 2-day working meeting, where all the experts involved will discuss and collaborate in an interactive setting.
 
   
  +
# '''Experts’ short papers sharing.''' The selected experts will be challenged in expressing their vision w.r.t the fertile research emerged so far in Big Data Analytics, and proposing topics and actions that should drive the research road map in big data analytics in the next 10 years in Europe. Special emphasis will be given towards Societal Good and how the Big Societal Challenges of H2020 provide a fertile ground for Big Data Analytics research.
  +
# '''Worskshop.''' A full 2-days workshop will be held, with scientific interactive sessions and a final one dedicated at defining the structure of the position paper. A rapporteur will be appointed for each session with the task of collecting the contributions as well as the comments and live discussions during the sessions and editing them.
  +
# '''Position paper writing.''' The proposers together with the rapporteurs will produce a first draft of “white paper/roadmap report” based on the experts contributes, and on the discussion and reports produced during the workshop. The draft will be reviewed by the experts and finalized accordingly.
   
=== Workshop Venue ===
+
= Workshop =
  +
 
The workshop of the ERCIM Expert Group on Big Data will take place near Pisa, Italy, '''from May 29th to May 30th, 2014'''. It will be a full 2-day working meeting, where all the experts involved will discuss and collaborate in an interactive setting.
  +
  +
== Workshop agenda ==
  +
  +
Wednesday, May 28th, 2014
  +
* Evening: welcome cocktail / light buffet dinner
  +
  +
Thursday, May 29th, 2014
  +
* 9.00 [Plenary Meeting] Opening, presentations, discussion and set up of the working method.
  +
* 10.30 Coffee Break
  +
* 11.00 Parallel working sessions / 1
  +
* 13.00 Lunch
  +
* 14.30 Parallel working sessions / 2
  +
* 16.30 Coffee break
  +
* 17.00 [Plenary Meeting] Wrap-up of first day
  +
* 18.00 End of works
  +
* 20.30 Social dinner
  +
  +
Friday, May 30th, 2014
  +
* 9.00 Parallel working sessions / 3
  +
* 10.30 Coffee Break
  +
* 11.00 Parallel working sessions / 4
  +
* 13.00 Lunch
  +
* 14.30 [Plenary Meeting] Final wrap-up / white paper organization
  +
* 16.30 Coffee break
  +
* 17.00 [Plenary Meeting] Continuation of previous session
  +
* 18.00 End of works
  +
* 20.30 Dinner
  +
  +
  +
== Workshop Venue ==
   
 
The venue selected is Tirrenia, a small beach village ten kilometers from Pisa, and the hotel GreenPark has been selected: [http://www.greenparkresort.com Green Park Resort]
 
The venue selected is Tirrenia, a small beach village ten kilometers from Pisa, and the hotel GreenPark has been selected: [http://www.greenparkresort.com Green Park Resort]
  +
  +
== Directions and connections ==
   
 
Pisa is a well connected destination.
 
Pisa is a well connected destination.
   
The International '''Airport''' “Galileo Galilei” of Pisa is only 7 km away from the Conference Centre in Tirrenia. It has become one of the main Italian airports, with flights to over 74 destinations all around Europe, United States and Russia. Info: [http://www.pisa-airport.co Pisa Airport]
+
* The International '''Airport''' “Galileo Galilei” of Pisa is only 7 km away from the Conference Centre in Tirrenia. It has become one of the main Italian airports, with flights to over 74 destinations all around Europe, United States and Russia. Info: [http://www.pisa-airport.co Pisa Airport]
   
The '''railroad''' line connects Pisa with the rest of Italy allowing you to get to Florence in 45 mins as well as Rome and Milan in under 3 hours. The main station is located in the city centre. Info: [http://www.trenitalia.it Trenitalia]
+
* The '''railroad''' line connects Pisa with the rest of Italy allowing you to get to Florence in 45 mins as well as Rome and Milan in under 3 hours. The main station is located in the city centre. Info: [http://www.trenitalia.it Trenitalia]
   
Tirrenia is connected via hourly '''bus''' to Pisa station. Info: [http://www.cpt.pisa.it/orari/extra/lineeLoc/elencoLin/TIRRENIA.htm Time Tables]
+
* Tirrenia is connected via hourly '''bus''' to Pisa station. Info: [http://www.cpt.pisa.it/orari/extra/lineeLoc/elencoLin/TIRRENIA.htm Time Tables]
   
== Experts List ==
+
= Experts List =
   
  +
* Anastasia Ailamaki, EPFL
List to be finalized
 
  +
* Emanuele Baldacci, ISTAT
  +
* Peter Baumann, Jacobs University
  +
* Francesco Bonchi, Yahoo! Labs
  +
* Guido Caldarelli, IMT
  +
* Martin Kersten, CWI
  +
* Alexander Löser, Beuth hochschule
  +
* Stan Matwin, Dalhousie University
  +
* Dunja Mladenic, J. Stefan Institute
  +
* Amedeo Napoli, LORIA
  +
* Dino Pedreschi, University of Pisa
  +
* Nicolas Spyratos, Paris-South – Orsay
  +
* Michalis Vazirgiannis, LIX Ecole Polytechnique

Revision as of 13:02, 22 May 2014

Big Data Analytics Expert Group

Aim and context

The objective of this Expert Group is to gather experts on the many faces of Big Data Analytics and compile with their help a white paper that fosters a future agenda for European research on this direction.

Sensing big data at a societal scale, and the transparent interlinking of digital and physical reality, has the potential of providing a powerful social microscope, which can help us understand many complex and hidden socio-economic phenomena, such as mobility behaviors, economic and financial crises, the spread of epidemics, the diffusion of opinions and so on. It is clear that such challenge requires high-level analytics, modeling and reasoning across all the social dimensions.

In practice, however, there is a big gap from the opportunities offered by the big data to the challenges posed by social, economical, scientific phenomena: Big data are fragmented and low-level. They reside in diverse databases and repositories, often inaccessible for proprietary and legal constraints, and have limited power to portray different social dimensions. There are many regulatory, business and technological barriers to set the power of big data free.

As a response, the paradigm of Big Data Analytics is emerging at the convergence of several disciplines, including machine learning, data mining, statistics, complex systems, socioeconomic sciences, etc. There is a flourishing body of research about making sense of Big Data, but a coherent scientific and technological framework is still missing. We need to put at work scientists and technologists from different disciplines to shape a research and innovation agenda that might drive the ERICM future actions.

We propose here a group that involves prominent research leaders in industry and academia to share their visions and elaborate together what should be the challenging research issues in this promising research frontier.

Organization team

  • Fosca Giannotti, ISTI-CNR
  • Mirco Nanni, ISTI-CNR
  • Andreas Rauber, TU Wien
  • Costantino Thanos, ISTI-CNR

Method of work

The activity of the Expert Group is planned along three steps:

  1. Experts’ short papers sharing. The selected experts will be challenged in expressing their vision w.r.t the fertile research emerged so far in Big Data Analytics, and proposing topics and actions that should drive the research road map in big data analytics in the next 10 years in Europe. Special emphasis will be given towards Societal Good and how the Big Societal Challenges of H2020 provide a fertile ground for Big Data Analytics research.
  2. Worskshop. A full 2-days workshop will be held, with scientific interactive sessions and a final one dedicated at defining the structure of the position paper. A rapporteur will be appointed for each session with the task of collecting the contributions as well as the comments and live discussions during the sessions and editing them.
  3. Position paper writing. The proposers together with the rapporteurs will produce a first draft of “white paper/roadmap report” based on the experts contributes, and on the discussion and reports produced during the workshop. The draft will be reviewed by the experts and finalized accordingly.

Workshop

The workshop of the ERCIM Expert Group on Big Data will take place near Pisa, Italy, from May 29th to May 30th, 2014. It will be a full 2-day working meeting, where all the experts involved will discuss and collaborate in an interactive setting.

Workshop agenda

Wednesday, May 28th, 2014

  • Evening: welcome cocktail / light buffet dinner

Thursday, May 29th, 2014

  • 9.00 [Plenary Meeting] Opening, presentations, discussion and set up of the working method.
  • 10.30 Coffee Break
  • 11.00 Parallel working sessions / 1
  • 13.00 Lunch
  • 14.30 Parallel working sessions / 2
  • 16.30 Coffee break
  • 17.00 [Plenary Meeting] Wrap-up of first day
  • 18.00 End of works
  • 20.30 Social dinner

Friday, May 30th, 2014

  • 9.00 Parallel working sessions / 3
  • 10.30 Coffee Break
  • 11.00 Parallel working sessions / 4
  • 13.00 Lunch
  • 14.30 [Plenary Meeting] Final wrap-up / white paper organization
  • 16.30 Coffee break
  • 17.00 [Plenary Meeting] Continuation of previous session
  • 18.00 End of works
  • 20.30 Dinner


Workshop Venue

The venue selected is Tirrenia, a small beach village ten kilometers from Pisa, and the hotel GreenPark has been selected: Green Park Resort

Directions and connections

Pisa is a well connected destination.

  • The International Airport “Galileo Galilei” of Pisa is only 7 km away from the Conference Centre in Tirrenia. It has become one of the main Italian airports, with flights to over 74 destinations all around Europe, United States and Russia. Info: Pisa Airport
  • The railroad line connects Pisa with the rest of Italy allowing you to get to Florence in 45 mins as well as Rome and Milan in under 3 hours. The main station is located in the city centre. Info: Trenitalia
  • Tirrenia is connected via hourly bus to Pisa station. Info: Time Tables

Experts List

  • Anastasia Ailamaki, EPFL
  • Emanuele Baldacci, ISTAT
  • Peter Baumann, Jacobs University
  • Francesco Bonchi, Yahoo! Labs
  • Guido Caldarelli, IMT
  • Martin Kersten, CWI
  • Alexander Löser, Beuth hochschule
  • Stan Matwin, Dalhousie University
  • Dunja Mladenic, J. Stefan Institute
  • Amedeo Napoli, LORIA
  • Dino Pedreschi, University of Pisa
  • Nicolas Spyratos, Paris-South – Orsay
  • Michalis Vazirgiannis, LIX Ecole Polytechnique