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Complexity Science Hub Vienna

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The Complexity Science Hub Vienna (CSH) is a Vienna-based research organisation with the aim to bundle, coordinate and advance the research of complex systems, system analysis and big data science in Austria.

Organization

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The CSH was founded in 2015 as a joint initiative to foster big data science for the benefit of society and to increase the international visibility of Austrian complexity research.[1] The official start was in 2016.[2] Since May 2016 the CSH has been located in Palais Strozzi in Vienna.

The first four member institutions were the TU Wien, the Graz University of Technology, the Medical University of Vienna and the AIT Austrian Institute of Technology.[3] In 2016, the Vienna University of Economics and Business, and the International Institute for Applied System Analysis (IIASA) became members of the CSH.[4] Further members are the Danube University Krems[5] and Austrian Economic Chambers (since 2018), the Institute of Molecular Biotechnology IMBA and the University of Veterinary Medicine Vienna (since 2019), and the Central European University (since 2020).

The CSH is embedded in an international network of complexity research centers and universities, including the Santa Fe Institute in New Mexico, Nanyang Technological University in Singapore, Arizona State University, and the Institute for Advanced Study (IAS) in Amsterdam. Since April 2017, there has been a partnership with the Central European University in Budapest.[6]

Complexity scientist Stefan Thurner has been the first president and scientific director of the CSH since its foundation. The international science advisory board is chaired by the Austrian sociologist Helga Nowotny.

Research

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The main topics of research at the CSH include:[7]

  • theoretical foundations of complexity science (f.i. properties of complex systems, entropy of complex systems, statistical mechanics, the origin of Power laws, the mathematics of collapse, evolution and co-evolution, path dependence, Agent-based models)[8][9]
  • health and medicine (efficiency and resilience of health care systems, based on health care data; personalized medicine; disease prediction and prevention)[10][11]
  • Systemic risk (Why do complex systems such as banking networks collapse? What is the likelihood of collapse? Can collapse be predicted? How to build a complex system to be stable? )[12][13]
  • Cities ("Science of Cities") (How can data be used for the benefit of cities, the population, the administration ("Smart city")? How do cities become more sustainable? How to increase citizen participation? Is there a direct link between city size and city life?)
  • the "Internet of things" (Does a more efficient production automatically lead to more vulnerability? How secure is a fully digitized production when it comes to attacks? How can sensor data be used to answer systemic questions?)
  • computational social science (Opinion formation in social networks and heterogeneous societies.[14] How do conflicts arise? How can conflicts be solved? What is the difference between networks of men and women?)[15]
  • big data analytics (Do we lose our privacy? Is social media a threat to democracy?[16] How can fake news be identified?[17] What does social media say about gender?[18][19] Agent-based and big data models of society [20][21])

References

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  1. ^ "Big Data mit Sinn: "Complexity Science Hub Vienna" nimmt Arbeit auf". APA Science. July 28, 2015. Retrieved March 11, 2019.
  2. ^ "Phantastische Dinge mit Big Data tun: Neue Forschungsstelle in Wien". Der Standard. May 18, 2016. Retrieved November 28, 2018.
  3. ^ "Complexity Science Hub Vienna nimmt Arbeit auf". Der Standard. July 28, 2015. Retrieved Nov 26, 2018.
  4. ^ "IIASA joins Complexity Science Hub Vienna". IIASA. May 23, 2016. Retrieved Nov 26, 2018.
  5. ^ "Donau-Universität Krems ist neues Mitglied im Complexity Science Hub Vienna". Wirtschaftszeit. Oct 25, 2018. Retrieved Nov 26, 2018.
  6. ^ "Complexity Science Hub Vienna Supports CEU". CEU. April 25, 2017. Retrieved Nov 26, 2018.
  7. ^ "Research fields at the CSH". Retrieved November 28, 2018.
  8. ^ Thurner S, Hanel R, Klimek P (2018). Introduction to the theory of complex systems. Oxford University Press. ISBN 978-0-19-186106-2.
  9. ^ Thurner S, Corominas-Murtra B, Hanel R (2017). "Three faces of entropy for complex systems: Information, thermodynamics, and the maximum entropy principle". Physical Review E. 96 (3). arXiv:1705.07714. doi:10.1103/PhysRevE.96.032124.
  10. ^ "Personalisierte Therapie mindert Krebsrisiko für Diabetiker". Der Standard. November 8, 2016. Retrieved November 28, 2018.
  11. ^ "'Internet der Kühe' soll Gesundheit von Tier und Mensch verbessern". Der Standard. Nov 5, 2018. Retrieved Nov 28, 2018.
  12. ^ Poledna S, Thurner S (2016). "Elimination of systemic risk in financial networks by means of a systemic risk transaction tax". Quantitative Finance. 16 (10): 1599–1613. arXiv:1401.8026. doi:10.1080/14697688.2016.1156146.
  13. ^ "Systemic Risk: The Continuing Quest for Models to Monitor and Manage the Ultimate Challenge to Financial Stability". GARP. September 1, 2016. Retrieved November 28, 2018.
  14. ^ "Complex Systems Theorists Explain Why Democracy Is Dying". VICE (Motherboard). Nov 27, 2018. Retrieved Nov 30, 2018.
  15. ^ Garcia D (2017). "Leaking privacy and shadow profiles in online social networks". Science Advances. 3 (8): e1701172. doi:10.1126/sciadv.1701172. hdl:20.500.11850/238031.
  16. ^ "Information Spookyhighway #470 speaks with David Garcia". Scienceforthepeople.org. April 20, 2018. Retrieved November 28, 2018.
  17. ^ "Physiker: Fake News lassen sich allein an Netzwerkstruktur erkennen". Der Standard. Dec 10, 2017. Retrieved November 28, 2018.
  18. ^ "Researchers are using facebook data to study gender inequality". mic network. July 13, 2018. Retrieved Nov 28, 2018.
  19. ^ "Why Do More Men Use Facebook in These Countries?". Inverse. June 24, 2018. Retrieved Nov 28, 2018.
  20. ^ "Studie: Keine Muster in Erfolgsläufen von Künstlern und Forschern". APA Science. July 11, 2018. Retrieved Nov 28, 2018.
  21. ^ Poledna S, Hinteregger A, Thurner S (2018). "Identifying Systemically Important Companies by Using the Credit Network of an Entire Nation". Entropy. 20 (10). doi:10.3390/e20100792.
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