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== Big Data Analytics Expert Group == |
== Big Data Analytics Expert Group == |
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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. |
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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. |
Revision as of 12:38, 22 May 2014
Big Data Analytics Expert Group
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
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 Venue
The venue selected is Tirrenia, a small beach village ten kilometers from Pisa, and the hotel GreenPark has been selected: Green Park Resort
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
List to be finalized