Scientific Data Visualization

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Afternoon workshop organised by PhDs for PhDs.

Scientific Data Visualization Workshop

29 June 2017
14.00-18.00, followed by an Apéro
ETH Hönggerberg, HCI G 7

flyer (PDF, 914 KB)

This workshop is designed for PhD students. The workshop is free of charge, but the seats are limited.

Please register by using the form below.

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Let’s face it: your time as a PhD student is all about how to do correct science and to sum it up into a paper. However, questions like how a good overview graphic is put together, which colours should one use in which context, or how data is clearly arranged, seem to be of less importance. Science matters and not nice pictures, right?

The best science is worthless if it is not well communicated and thus not well understood by editors, reviewers, investors, decision makers or tax payers. Schemes, graphs and figures are the key tools to communicate your science in an intuitive way. You, as a young researcher, have to adapt to the present and future demands of the scientific world. Hence, adequate graphical skills are essential in order to stay competitive.

With the Scientific Data Visualization Workshop we put together an afternoon of talks from experts in the field of data visualization. The talks range from a scientific- to a graphical background. During 45 min lectures you will learn, for example on the basis of negative examples, how to best visualize the important points of your work! Each talk is followed by a Q&A session. During an Apéro there will be time to network and further discuss visualization ideas.

Abstracts of Speakers

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Expressive & Effective Data Visualization (Schulz)

After months of measurements and countless hours of data cleaning and processing, you got exciting results that point towards entirely new scientific insights. Graphing that data occurs to you as an afterthought when writing the paper or putting together the poster or slide stack. Nothing complicated, just a few mouse clicks in your favorite spreadsheet software and done! Good enough.

Or is it? Is that diagram really expressive of your data – i.e., a true and honest depiction of your data and only your data? Could it be misread by showing features that are not actually in the data? Could critical viewers even come to the conclusion that you wanted to mislead them? Would there be a way for these critics to check your diagram for plausibility, maybe even reproduce it? And if it is a valid representation of your data, is it also effective for highlighting your results – i.e., does it convey what you want to show about your data? Can viewers easily pick up on the points you’re trying to make with that graphic? Or do you need a long figure caption to explain how to read your diagram, what can be observed in it, and why this is important?

This talk will provide you with a basic understanding of the Do’s and Don’ts of data visualization – chart types, scales, colors, labels, legends, etc. It will be accompanied by a multitude of examples showing best and worst case data visualizations, so that you get a concrete idea of the pitfalls to look for in your diagrams, as well as when reviewing the work of others, and how to fix them.

Note: You can submit your diagram, figure, or chart to the speaker for a chance of it being discussed anonymously as one of the examples in the talk. To get your graphic considered simply email it in PNG or PDF format together with a brief description to  by 16 June 2017.

Dr. Hans-Jörg Schulz

Dr. Hans-Jörg Schulz received his PhD from the University of Rostock, Germany in 2010 with a thesis on “Explorative Graph Visualization”. He has since worked in the areas of Visual Analytics and Information Visualization, with extended research stays at IBM Research in the US, TU Graz in Austria, and Fraunhofer IGD in Germany. He is currently working as a Senior Researcher at the Institute of Computer Science at the University of Rostock, while pursuing his research interests in general visualization concepts and specific visualization techniques for climate research and the life sciences.

Please note: your registration is only complete after you have received a confirmation e-mail (two-step registration).

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Tue May 23 02:50:08 CEST 2017
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