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Big Data and Data Science

Complex systems research, data science and the processing of large amounts of data are key challenges facing the applied research sector in the field of information and communication technology. They were therefore the focus of this year’s annual meeting of RSA FG with 70 attendees (employees, members of the Advisory Board and speakers).

How does one raise awareness of data science in one’s own research? By discussing it with experts who would appear to have nothing to do with one’s own field of research.

Univ. Prof. Mag. DDr. Stefan Thurner, Director of the Institute of the Science of Complex Systems at the Medical University of Vienna, presented a fascinating concept in his keynote speech titled “Complex Systems Research: Data-driven advances and applications”.

Complex systems (systematically?) permeate our living environments

Living systems are the classic example of complex systems. Cells, for example, consist of many interacting chemical substances that greatly influence each other (proteins, RNA, DNA, etc.), whose production they themselves control via so-called gene regulation networks. At a higher level, cell groups form complex systems with the brain as the best-known example. At a still higher level, complex systems are formed from interactions between individuals: societies. These include ant colonies as well as participants in online multiplayer games, road traffic, brokers at the stock exchange, and entire economies. All of these systems have specific dynamic properties in common; in addition, they share robustness, adaptability and susceptibility to collapse beyond certain critical points.

Thurner’s summary: “The main goal is to enable methodological and conceptual breakthroughs in sciences that are heavily data-driven. As is now common in the life sciences, but is only just beginning in the social sciences.”


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