Invited Talk: Marc Streit on "What comes first? Visual Analysis of Multi-Attribute Rankings" (September 26, 2013)

Gespeichert von Bilal Alsallakh am

Portrait of Marc StreitAs part of the monthly VRVisForum organized by VRVis , Assistant Professor Marc Streit from Johannes Kepler University of Linz will talk about:

"What comes first? Visual Analysis of Multi-Attribute Rankings”

 

When: 26. Sept 2013 at 15:00 - 16:30

 

Where: Tech Gate Vienna room 3.2

 

Abstract: Rankings are omnipresent. They have the important function of helping us to navigate content and provide guidance as to what is considered “good”, “popular”, “high quality”, and so on.  In the first part of the talk, I will introduce LineUp, a novel visualization for creating, analyzing, and comparing multi-attribute rankings. LineUp allows us, for example, to prioritize tasks or to evaluate the performance of universities relative to each other. The technique supports the ranking of items based on multiple heterogeneous attributes with different scales and semantics. It enables users to interactively combine attributes and flexibly refine parameters to explore the effect of changes in the attribute combination.
In the second part of the talk, I will focus on solutions designed to support analysts in making sense of large, heterogeneous datasets. In particular, I will discuss our recent work on cancer subtype analysis as well as techniques for investigating multi-dimensional data in the context of biological networks. Both projects are embedded in the Caleydo project (http://www.caleydo.org)..

 

Biography: Marc Streit is assistant professor at the Institute of Computer Graphics, Johannes Kepler University Linz, Austria. He finished his PhD at Graz University of Technology in early 2011 and moved to Linz later that year. As part of his tenure-track position, he spent a part of the year 2012 as a visiting researcher at the Center for Biomedical Informatics at Harvard Medical School. His scientific areas of interest include Information Visualization, Visual Analytics, and Bioinformatics, where he is particularly interested in the integrated analysis of large heterogeneous data.