Challenges in Data Science:
a Complex Systems Perspective

Complex Systems Science is mainly expected to contribute new paradigms for modelling, representing and extracting information about structures and dynamics in systems characterized by interacting elements, thus providing new clues and perspectives to the classical data mining tasks like classification or regression. Data are key ingredients for understanding the increasingly complex social, economic & technological systems. Relevant datasets are growing in size and becoming increasingly heterogeneous. Financial systems, biological and physiological records, geographic map, 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. A Complex Systems perspective can add clues to a number of issues, in order to achieve efficient interoperability and performances, reduced risks and increase overall knowledge.

This website gathers ongoing and past initiatives (workshops, meetings) aimed at the exploration of the multiple methodological intersections devised in diverse application areas.