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Excellent expertise has been gained thanks to the involvement in several EU projects, as GeoPKDD( and MODAP ( 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.