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CNRCNR, the Italian National Research Council, is the main public Italian research institution, it employs more than 4000 researchers in 100 Institutes across Italy. CNR participates to this project with two institutes: the Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo” (ISTI) and the Istituto di Informatica e Telematica (IIT) both located in Pisa. Before presenting the two institutes, it is worth mentioning that ISTI and IIT in 2013 co-funded the European laboratory on Big Data Analytics and Social Mining (, one of the pillars of this project, aimed at pursuing interdisciplinary research initiatives connected to the impulse that “big data” and ICT are having on (socio-economic) sciences. One of the goal is 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. CNR participates in the project with the researchers of 5 different groups presented below. 

KDD - ISTI ( founded in 1996, is aimed at pursuing fundamental research, strategic applications and higher education in the area of Knowledge discovery and Data Mining and is a joint initiative with University of Pisa. It is today a leading research hub on mobility data mining and privacy preserving 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, Toyota) 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). 

Nemis- ISTI participates with its InfraScience Research Group (lead by Dr. Donatella Castelli), has a long track of EC funded projects aimed at designing and operating data infrastructures. Members of this team have scientifically coordinated the projects DILIGENT, D4Science, D4Science-II, iMarine that have played a central role in the definition and implementation of data infrastructures and Virtual Research Environments. Currently, they are also coordinating the technical development of OpenAIRE, the Open Access Infrastructure for Research in Europe. The team is also a partner in the Research Data Alliance Europe initiative and in ENVRI, the cluster of ESFRI Research Infrastructures on Environment.

HPC - ISTI ( carries out research on algorithms and systems addressing computational and data-intensive problems arising in scientific, business, social, and knowledge-based applications. Our advanced solutions exploit high-performance techniques and tools to deal with the exponential growth of users, data, knowledge and services that need to be efficiently stored, managed, analysed and retrieved. The main research topics are: Web Search, Data and Web Mining, Cloud Computing. The group is composed of about 20 people involved in several projects including the running EC projects Midas, Contrail, IngeoClouds, eCloud, and the national projects Secure!, RIS and MOTUS.

WAFI-IIT has followed the evolution of the World Wide Web from the success of markup languages, to the introduction of a semantic layer and the explosion of the social web content. WAFI-IIT studies the evolution of the Web in all its forms (data, communities, technologies, guidelines, recommendations, 

designs, software, tools). Currently, WAFI-IIT performs research and development activities on Social Media Analysis, spanning from Social Network Analysis to Social Sensing and Social Media Intelligence, Information Visualization on the Web, Mashup Applications, Open and Big Data, Web Mining, Semantic Web. It is also part of the Italian W3C office, involved in the organization of events and courses on Linked Open Data.

UI-IIT research activities are focused on the Future Internet design and evaluation, mobile and online social networks being one of the key research topics the group is focusing on. UI-IIT research also focuses on analysis of users’ behaviour in Online Social Networking environments, collection and analysis of large- scale datasets in these environments, and development of models of social relationships. Moreover, UI-IIT researchers feature a broad expertise in the design, modelling, performance evaluation through analysis, simulation and experiments of innovative Internet architectures and protocols in various types of networking environments. UI-IIT members are actively participating to relevant expert groups at the national and European levels, and have been involved in the EC FIRE consultations since the beginning.


Role in the Project

CNR coordinates the project and leads WP7 virtual access and WP 10 on the SoBigData RI. It will contribute to all three kind of activities with special focus on integrating the many methods for social sensing and social mining from the national infrastructure; creating the new pan-European SoBigData RI; its enrichment with new research methods through JRAs; and on providing transactional and virtual access.


Infrastructure brought into the project

CNR in 2013 has promoted the European laboratory on Big Data Analytics and Social Mining SoBigData, 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. The infrastructures of are entirely brought into the project. They are articulated on various themes: network analytics, mobility analytics, social sensing, text mining, indexing and search. Moreover, they comprise a vast repertoire of big data resources, including mobile phone call records, social networking records, GPS tracks from navigation devices, supermarket transaction records, web search query logs, etc. 



EU Project

See the websites for EU Projects 654024 and 871042 for more details is licensed under a Creative Commons Attribution 4.0 International License