Understanding complex systems: When Big Data meets network science
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Ingo Scholtes
Ingo Scholtes is a senior researcher at the Chair of Systems Design at ETH Zürich. Following studies in computer science and mathematics, he completed his doctorate studies in the Systems Software and Distributed Systems group at the University of Trier in 2011. He was involved in the Large Hadron Collider experiment at CERN, designing and implementing a Peer-to-Peer-based framework for large-scale data distribution which is since being used to monitor particle collision data from the ATLAS detector. Inspired by this experience, he turned his attention to the modeling and analysis of complex networked systems. His latest research addresses applications of network science in the analysis of data from socio-technical systems, but also from biology and sociology. In a theoretical line of research he further studies new methods in the analysis of time-stamped network data. At ETH Zürich he developed a course on network science which bridges the curricula of engineering and natural sciences. He previously held a scholarship from the Studienstiftung des Deutschen Volkes and was awarded a Junior-Fellowship from the Gesellschaft für Informatik in 2014.
ETH Zürich, Chair of Systems Design, CH-8092 Zürich, Switzerland
Abstract
Better understanding and controlling complex systems has become a grand challenge not only for computer science, but also for the natural and social sciences. Many of these systems have in common that they can be studied from a network perspective. Consequently methods from network science have proven instrumental in their analysis. In this article, I introduce the macroscopic perspective that is at the heart of network science. Summarizing my recent research activities, I discuss how a combination of this perspective with Big Data methods can improve our understanding of complex systems.
About the author
Ingo Scholtes is a senior researcher at the Chair of Systems Design at ETH Zürich. Following studies in computer science and mathematics, he completed his doctorate studies in the Systems Software and Distributed Systems group at the University of Trier in 2011. He was involved in the Large Hadron Collider experiment at CERN, designing and implementing a Peer-to-Peer-based framework for large-scale data distribution which is since being used to monitor particle collision data from the ATLAS detector. Inspired by this experience, he turned his attention to the modeling and analysis of complex networked systems. His latest research addresses applications of network science in the analysis of data from socio-technical systems, but also from biology and sociology. In a theoretical line of research he further studies new methods in the analysis of time-stamped network data. At ETH Zürich he developed a course on network science which bridges the curricula of engineering and natural sciences. He previously held a scholarship from the Studienstiftung des Deutschen Volkes and was awarded a Junior-Fellowship from the Gesellschaft für Informatik in 2014.
ETH Zürich, Chair of Systems Design, CH-8092 Zürich, Switzerland
©2015 Walter de Gruyter Berlin/Boston
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- Frontmatter
- Editorial
- Autonomous driving
- Special Issue
- Conditions for a safe state of automated road vehicles
- Automated driving on public roads: Experiences in real traffic
- Vision-only fully automated driving in dynamic mixed-traffic scenarios
- Perception sensor modeling for virtual validation of automated driving
- Self-Portrayals of GI Junior Fellows
- Understanding complex systems: When Big Data meets network science
- Distinguished Dissertations
- Quantifying and protecting location privacy
Articles in the same Issue
- Frontmatter
- Editorial
- Autonomous driving
- Special Issue
- Conditions for a safe state of automated road vehicles
- Automated driving on public roads: Experiences in real traffic
- Vision-only fully automated driving in dynamic mixed-traffic scenarios
- Perception sensor modeling for virtual validation of automated driving
- Self-Portrayals of GI Junior Fellows
- Understanding complex systems: When Big Data meets network science
- Distinguished Dissertations
- Quantifying and protecting location privacy
