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The Knowledge Discovery and Data Mining Laboratory (KDD Lab) is a joint research initiative of ISTI Institute of CNR and the Department of Computer Science of the University of Pisa.

The objective of the research unit is the development of theory, techniques and systems for extracting and delivering useful knowledge out of large masses of data.

Today, knowledge discovery and data mining is both a technology that blends data analysis methods with sophisticated algorithms for processing large data sets, and an active research field that aims at developing new data analysis methods for novel forms of data. On one side, classification, clustering and pattern discovery tools are now part of mature data analysis and Business Intelligence systems and have been successfully applied to problems in various commercial and scientific domains. On the other side, the increasing heterogeneity and complexity of the new forms of data – such as those arriving from medicine, biology, the Web, the Earth observation systems, the mobility data arriving from wireless networks – call for new forms of patterns and models, together with new algorithms to discover such patterns and models efficiently.

In this context, the mission of the KDD laboratory is to pursue fundamental research, strategic applications and higher education.

Research

It was 1999 when we approached data mining research field. Our exploration of the world of Data is still continuing...

Excellent expertise has been gained thanks to the involvement in several EU projects, as GeoPKDD(www.geopkdd.eu) and MODAP (www.modap.eu). A concrete recent achievement is the realization of the system M-ATLAS as an platform to support the mobility knowledge discovery process, from data preprocessing, to data mining to semantic enrichment and patterns interpretation.

The main research track of KDDLab in the field of Complex Networks is Multidimensional Network Analysis. Traditionally, Complex Network Analysis has been monodimensional: researchers focused their attention to network with a single kind of relation represented. KDDLab is pushing the research over multidimensional networks, i.e. network with multiple kind of relations, since they are a better model to represent the complexity in reality (transportation, infrastructure and social networks are often multidimensional).

In the era of Big Data the opportunities of discovering knowledge from social big data increase with the risk of privacy and discrimination violation. However, big data analytics and fairness are not necessarily enemies. Sometimes many practical and impactful services based on big data analytics can be designed in such a way that the quality of results can coexist with discrimination and privacy protection. The solution is the application of the privacy-by-design and discrimination-by-design principles.

One of the most pressing and fascinating challenges scientists face today, is understanding the complexity of our globally interconnected society. The big data arising from the digital breadcrumbs of human activities promise to let us scrutinize the ground truth of individual and collective behaviour at an unprecedented detail and scale. There is an urgent need to harness these opportunities for scientific advancement and for the social good. The main obstacle to this accomplishment, besides the scarcity of data scientists, is the lack of a large-scale open infrastructure, where big data and social mining research can be carried out.

EU Datathon 2018

Start:
2018/05/22 09:00 Europe/Rome
End:
2018/10/02 18:00 Europe/Rome
Location:
Brussels, Belgium
Link:
EU Datathon 2018
Description:

The Publications Office of the European Union is organising the second edition of the EU Datathon competition that highlights the potential of linking EU and national data.
The event started in May 2018, with the final phase taking place in Brussels on 2 October 2018.

The 5th IEEE International Conference on Data Science and Advanced Analytics

Start:
2018/10/01 09:00 Europe/Rome
End:
2018/10/04 18:00 Europe/Rome
Location:
Turin, Italy
Link:
The 5th IEEE International Conference on Data Science and Advanced Analytics
Description:

The IEEE International Conference on Data Science and Advanced Analytics (DSAA) aims to be the flagship annual meeting spanning the interdisciplinary field of Data Science. DSAA focuses on the science of data science, as well as the implications of the science for applications to industry, government, and society.

Soccer Data Challenge 2018

Start:
2018/10/12 07:30 Europe/Rome
End:
2018/10/13 20:00 Europe/Rome
Location:
Pisa, Italy
Link:
Soccer Data Challenge 2018
Description:

La Soccer data challenge è una competizione aperta a tutti gli appassionati di dati e calcio, che si svolgerà a Pisa il 12 e 13 ottobre 2018.
Per 30 ore consecutive, le squadre partecipanti si sfideranno sullo sviluppo di una soluzione per l’analisi di partite di calcio.

A loro disposizione avranno i dati di una intera stagione di serie A: oltre 500mila record, un dataset che contiene tutti gli eventi di gioco di ogni partita, definiti in ogni possibile aspetto.

La squadra vincitrice si aggiudicherà un premio di 5.000 euro.

Publications

Fun Facts


3
Gigabytes of data produced by a single person each year
3100
Millions of Internet users
500
Millions of Tweets sent per day
2300
Gigabytes of Internet traffic per day

Contacts

Need info? Want ideas? Write us!

Address @ ISTI

KDD Lab
Istituto di Scienza e Tecnologie dell’Informazione
Area della Ricerca CNR
via G. Moruzzi 1
56124 Pisa, Italy

Address @ UniPi

KDD Lab
Dipartimento di Informatica
Università di Pisa
Largo B. Pontecorvo 3
56127 Pisa, Italy

Phone Number

Phone: +39 050 621 3013
Fax: +39 050 315 2040

Email

kddlab-info@isti.cnr.it

Largo B. Pontecorvo 3
56127 Pisa
Italy
via Moruzzi 1
56124 Pisa
Italy