The role of Visual Analytics in Exploring Graph Data
University of Konstanz, Germany
Sophisticated algorithms are the central part of most graph analysis and graph drawing methods. Many clearly specified problems can be solved using algorithmic methods, but in some cases fully automatic methods are not enough to understand the complex graph data and draw valid conclusions. Humans with their abilities – their background knowledge, their creativity, and their judgment – need to be an integral part of the analysis process. This is where the research field of visual analysis comes into play: It tries to integrate automatic data analysis methods with interactive visualization techniques to support the human in gaining new insights. In this presentation, we will discuss the role of the human in the process of exploring and analyzing large graphs, and will illustrate the exiting potential of current Visual Analytics techniques as well as their limitations with several application examples.
Daniel A. Keim is professor and head of the Information Visualization and Data Analysis Research Group in the Computer Science Department of the University of Konstanz, Germany. He has been actively involved in data base, data analysis, and information visualization research for more than 20 years and developed a number of novel visual analysis techniques for large data sets. He has been program co-chair of the IEEE InfoVis and IEEE VAST symposia as well as the SIGKDD conference, and he is or was member of the IEEE InfoVis & IEEE VAST as well as EuroVis steering committees.
Dr. Keim got his Ph.D. and habilitation degrees in computer science from the University of Munich, Germany. Before joining the University of Konstanz, Dr. Keim was associate professor at the University of Halle, Germany and Technology Consultant at AT&T Shannon Research Labs, NJ, USA.
Distributed Computing: Graph Drawing Unplugged
ETH Zurich, Switzerland
Computer networks and distributed systems are typically represented as graphs, and sooner or later everybody working in distributed computing is facing a graph drawing problem. In my talk I will discuss a few artifacts (and open problems) in distributed computing that are related to graph theory and graph drawing. The focus of my talk will be wireless communication networks. While a vertex in a wireless network is simply some kind of communication device, vertices are not necessarily connected by edges, but rather “unplugged”.
Roger Wattenhofer is a full professor at the Information Technology and Electrical Engineering Department, ETH Zurich, Switzerland. He received his doctorate in Computer Science in 1998 from ETH Zurich. From 1999 to 2001 he was in the USA, first at Brown University in Providence, RI, then at Microsoft Research in Redmond, WA. He then returned to ETH Zurich, originally as an assistant professor at the Computer Science Department. Roger Wattenhofer's research interests are a variety of algorithmic and systems aspects in computer science and information technology, currently in particular wireless networks, wide area networks, mobile systems, social networks, and physical algorithms. He publishes in different communities: distributed computing (e.g., PODC, SPAA, DISC), networking (e.g., SIGCOMM, MobiCom, SenSys), or theory (e.g., STOC, FOCS, SODA, ICALP). He recently published the book "The Science of the Blockchain".