Data Science is a key ingredient for understanding the increasingly complex social, economic & technological systems. Number and size of the relevant datasets is growing and becoming increasingly heterogeneous. Financial systems, map and mobility data, urban space usage, human  behavior and infrastructure are increasingly linked to each other to provide services to each single user of the global community  worldwide. Data and platform access  can add clues to solve a number of issues, in order to  achieve efficient interoperability and performances. However, data access may imply a number of risks, intrinsically related to the individual privacy and social security.

 

The main objective of the meeting is the  exploration of the multiple methodological intersections that have been devised in the diverse areas to provide insights regarding e.g. acquisition and analysis of complex networks, resilience and vulnerability, cybersecurity and privacy. Data Science & Complex Systems Science can borrow new ideas and techniques from each other contributing to the synergetic comprehension of both disciplines.  Complex Systems Science is mainly expected to contribute a new paradigms for representing and extracting information about structures and dynamics characterized by interacting elements, thus providing new clues in classical data mining tasks like classification or regression.  Ultimate aim of the meeting is to discuss current understanding and devise further applications of data science in  mapping complex networks evolution and interaction.