Skip to main content

Visualization paper recognised with IEEE VIS Test of Time Award

The paper "An Information-theoretic Framework for Visualization" wins prize at the IEEE VIS Conference

Professor Min Chen

Professor of Scientific Visualisation Min Chen is one of the papers authors

The IEEE VIS Test of Time Award is an accolade given to recognise published articles whose contents are still vibrant and useful today and have had a major impact and influence within and beyond the visualization community.

The award is presented at the annual IEEE VIS conference, with the hope of encouraging researchers to produce work that is forward looking and has transformational potential. IEEE is aiming to build on its heritage by encouraging participants to aspire to be writing the papers that will be relevant in 10 and 20 years.

Papers are selected for each of the three historic conferences (VAST, InfoVis and SciVis) by Test of Time Awards committees, appointed by the VIS Steering Committee. The decisions are based on objective measures such as numbers of citations, and more subjective ones such as the quality and longevity and influence of ideas, outreach, uptake and effect not only in the research community, but also within application domains and visualization practice.

This year VAST gave out a 10-year test of time award, InfoVis a 10- and 20-year award, and SciVis a 13, 14 and 25 year award.

Professor Min Chen is one of the authors of the paper entitled "An Information-theoretic Framework for Visualization", that was awarded the 13 years SciVis ToT award.

2010 (13 years SciVis ToT award):
An Information-theoretic Framework for Visualization
Min Chen and Heike Leitte
DOI: 10.1109/TVCG.2010.132

Examining visualization from an information-theoretic perspective is clearly a highly meaningful approach – given that visualization acts as an interface between users and their data, and thus always serves a purpose of communication. The seminal work by Chen and Jänicke outlines a tight relation between information theory and data visualization, and establishes a theoretic framework for studying visualization in terms of coding, noise, entropy, etc., also exemplifying a number of concrete cases, including a discussion of the visual mapping and the combination of overview and detail in visualization. This work impresses by its very high generality as well as its substantial power as an analytic basis for many of the most central visualization concepts. Right after publication, this work became an important foundation for further theoretic work in visualization research and represents now one of the few, central perspectives on visualization theory.


The IEEE VIS Conference, The premier forum for advances in visualization and visual analytics, will return in 2024. Keep up to date at