Active

where YOu Go is where you Are

Acronym: 
YOGA
Start Date: 
1 July 2012
End date: 
30 June, 2014
Founded by: 
Bilateral collaboration CNR-CNPQ
Project Web Site: 
http://yoga.isti.cnr.it
Research Line: 
Mobility Data Mining

Behavioral patterns can be extracted from the traces of past human activities through a semantic- enriched knowledge discovery process.
Here, positioning data are first transformed in semantically enriched trajectory data stored in a database. Then, mobility patterns, the most common movements emerging from data, are computed with data mining algorithms. A further semantic enrichment step is needed to give context-dependent meaning to the discovered patterns. New challenging research topics result from this work.

SEmantic Enrichment of trajectory Knowledge discovery

Acronym: 
SEEK
Start Date: 
1 March 2012
End date: 
28 February, 2015
Founded by: 
FP7-PEOPLE IRSES
Project Web Site: 
http://www.seek-project.eu
Research Line: 
Mobility Data Mining

SEEK is a Marie Curie Project (project N. 295179) funded by EU in the PEOPLE program as an IRSES 2011 scheme. This project funds the exchange of research personnel between participant organizations from EU to international partners and vice-versa for a total funded budget of 352.800 euro. The consortium includes 8 partners from Europe, Brazil and Canada.
The goal of the project is to investigate methods to extract meaningful knowledge from large amount of movement data by defining techniques for an advanced semantic-rich knowledge discovery process.

Business Intelligence applied on Coop Data

Acronym: 
BI-COOP
Contact: 
Ruggieri Salvatore
Giannotti Fosca

is an industrial R&D project funded by Unicoop, one of largest italian retail companies. KDDLab created a very large sales data warehouse, equipped with advanced BI solutions for strategic marketing and customer care based on data mining predictive analytics.

Computer science and legal methods for enforcing the personal rights of non-discrimination and privacy in ICT systems

Acronym: 
ENFORCE
Contact: 
Ruggieri Salvatore
Project Web Site: 
http://enforce.di.unipi.it/
Research Line: 
Privacy aware data analysis

The greater presence and pervasiveness of ICT in everyday life poses new concerns about personal rights such as non-discrimination and individual privacy. Since these concerns limit the practical applicability and the broad acceptance of advanced technologies, such as decision support systems (DSS) and location-based services (LBS), the diffusion of these applications relies on the existence of technical tools to enforce personal rights. Developing these tools requires a constant reference to what is legal and what is not, in measurable and formal terms.

Osservatorio Turismo Pisa

Acronym: 
OTP
Start Date: 
1 September 2011
End date: 
1 August, 2012
Project Web Site: 
http://matlaspisa.isti.cnr.it/turismo-pisa/
Research Line: 
Mobility Data Mining

The aim of the project is to study the touristic flows in Pisa thanks to the analysis and the integration of different types of data: GPS traces, GSM call, Flickr photos and social and demographical data.

DataSIM

Acronym: 
DataSIM
Start Date: 
1 October 2011
End date: 
1 September, 2014
Contact: 
Salvatore Rinzivillo
Project Web Site: 
http://datasim-fp7.eu
Research Line: 
Mobility Data Mining
Social Network analysis

DATSIM aims at providing an entirely new and highly detailed spatial-temporal microsimulation methodology for human mobility, grounded on massive amounts of Big data of various types and from various sources, e.g. GPS, mobile phones and social networking sites, with the goal to forecast the nation-wide consequences of a massive switch to electric vehicles, given the intertwined nature of mobility and power distribution networks.

Using Local Inference in Massively Distributed Systems

Acronym: 
LIFT
Start Date: 
30 November 2010
Founded by: 
FET-Open (Future and Emerging Technologies) unit of the European Commission within the 7th Framework Programme
Contact: 
Pedreschi Dino
Project Web Site: 
http://lift-eu.org
Research Line: 
Mobility Data Mining
Privacy aware data analysis

As the scale of today’s networked techno-social systems continues to increase, the analysis of their global phenomena becomes increasingly difficult, due to the continuous production of streams of data scattered among distributed, possibly resource-constrained nodes, and requiring reliable resolution in (near) real-time.

The goal of LIFT is to enable the local detection of global phenomena and the efficient and effective detection of phase changes in very large data streams, where it is impossible or ineffective to accumulate all data into a single place.

ORANGE Telecom Project

Acronym: 
ORANGE
Start Date: 
1 August 2011
Contact: 
Giannotti Fosca
Nanni Mirco
trasarti
Research Line: 
Mobility Data Mining

The aim of the project is the usage of the M-Atlas system on Orange GSM data to extract human mobility models.

In the first phase of the project we have proposed a case study on human mobility as perceived by Orange telecom infrastructure. Based on GSM data of roaming users, we tried to understand how visitors of a touristic area use the territory, with particular emphasis on visits to attractions.

Simulazione e Sistemi IDroinformatici per la Gestione delle Risorse IDriche

Acronym: 
SID&GRID
Start Date: 
1 April 2010
End date: 
1 April, 2013
Founded by: 
Regione Toscana
Contact: 
Claudio
Project Web Site: 
http://sidgrid.isti.cnr.it/
Research Line: 
Mobility Data Mining

The water resources management, currently subject to increasing human pressure and climate change scenarios, take part of the environmental challenges we must pay more attention to.

VisMaster

Acronym: 
VisMaster
Start Date: 
1 August 2008
End date: 
31 July, 2010
Founded by: 
European Community, Coordination Action
Project Web Site: 
http://vismaster.eu/

VisMaster is a European Coordination Action Project focused on the research discipline of Visual Analytics: One of the most important challenges of the emerging Information Age is to effectively utilise the immense wealth of information and data acquired, computed and stored by modern information systems. On the one hand, the appropriate use of available information volumes offers large potential to realize technological progress and business success.

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