CNR (National Research Council)


cnr-logoCNR is the Italian National Research Council, founded in 1923, is a public organization with the duty to carry out, promote, spread, transfer and improve research activities in every scientific and technological sector. CNR employs more than 4000 researchers in 100 Institutes across Italy. CNR participates to this proposal with ISTI: Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo” located in Pisa.

ISTI is one of the earliest European research centres fully targeted at computer science. ISTI had a pioneering role in the international ICT scene, since the 1950’s, when one of the first computers was realized in Pisa on a suggestion by Enrico Fermi, in collaboration between the University of Pisa and Olivetti. ISTI currently employs 100 researchers, and about 90 PhD students, graduate and post-doc staff.

ISTI is pursuing many interdisciplinary research initiatives connected to the impulse that “big data” and the ICT’s are having on science, and the socio-economic sciences in particular. ISTI researchers are involved in many projects at global scale, and maintains strong liaisons with the international ICT research at the highest levels, including the research centers of the major ICT, Web and telecom corporations. ISTI has a long lasting partnership with Computer Science Department of University of Pisa, with many common projects and laboratories, including the joint research lab on Knowledge Discovery and Data Mining, KDD Lab., whose scientific leaders Fosca Giannotti and Dino Pedreschi participate in this proposal.

KDD Lab. was founded in 1996 and is aimed at pursuing fundamental research, strategic applications and higher education in the area of Knowledge discovery and Data Mining. KDD Lab is the earliest research lab in data mining in Italy and one of the earliest in Europe and currently counts around 25 among researchers & postdocs.

It is today a leading research hub on mobility data mining, becoming a reference not only for the international research community but also for leading industrial and public operators, such as telecom providers (Orange, Wind, Telecom Italia) and mobility agencies of regional and municipal administrations. KDD Lab. has also created novel methods for mining social networks, aimed at discovering patterns, evolutionary rules, community structure and predictive rules. KDD Lab. led and participated to a stream of FET-Open projects on big data and social mining (see project section).

KDD Lab. has recently promoted the European laboratory on Big Data Analytics and Social Mining, dedicated to the creation of a knowledge infrastructure for the acquisition and analysis of big data from social media, online social networks and other sources aimed at the realization of large scale data analytics and simulation projects. To the purpose of this proposal, KDD Lab. aggregates the Laboratory of Agent Based Social Simulation at the ISTC-CNR in Rome leaded by Rosaria Conte. The team will bring its expertise on Big Data Analytics, mobility data mining and social network analysis as well as its expertise in building efficient analytical algorithms and systems.

In the project, CNR will investigate new methods for evolutionary and multidimensional pattern mining over complex network and will develop a knowledge infrastructure for Big data analytics targeted to social diffusion processes. It will also pursue the combination of evolutionary patterns with the global analytical models of complexity science to deliver better models for social contagion at small (regional, urban) scale as well as the mega-modeling framework to make big data analytics and models accessible to a wide range of users. CNR will also investigate CNR the interplay among cognitive, emotional and behavioural contagion.


List of up to 5 relevant publications, and/or products, services (including widely-used datasets or software), or other achievements relevant to the call content;

  1. F Giannotti, M Nanni, D Pedreschi, F Pinelli, C Renso, S Rinzivillo, R Trasarti. Unveiling the complexity of 
human mobility by querying and mining massive trajectory data. The VLDB Journal 20(5), 695-719 (2011)
  2. D. Wang, D. Pedreschi, C. Song, F. Giannotti, A.-L. Barabasi. Human mobility, social ties, and link 
prediction. Proc. ACM SIGKDD Int. Conf. on Knowledge discovery and data mining, p. 1100-1108. (2011)
  3. M. Berlingerio, M. Coscia, F. Giannotti, A. Monreale, D. Pedreschi. Multidimensional networks: foundations 
of structural analysis. World Wide Web 16(5-6): 567-593 (2013)
  4. R. Conte, C. Andrighetto, M. Campenni Minding norms: Mechanisms and dynamics of social order in agent 
societies. Oxford University Press, ISBN: 9780199812677 (2013).
  5. M. Coscia, F. Giannotti, D. Pedreschi, G. Rossetti. Uncovering hierarchical and overlapping communities 
with a local-first approach. ACM Transactions on Knowledge Discovery from Data. (2014) to appear.