Data Viz: Re-examining what we thought we knew

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Instead of well-run experiments and real evidence, many supposed rules are based on opinion, aesthetic judgments, and incomplete or oversimplified studies.

In this Data Science Central webinar, I will walk you through a number of things that we thought we knew, but that on closer inspection turned out to be wrong – it turned out that we didn’t know them, after all. Knowing what we know, what we don’t know, and what we merely assume, is important so we don’t rely on supposed rules that are not actually based on evidence. To figure out which is which, we have to keep asking a simple question: how do we know that?


About the speaker


Robert Kosara

Research Scientist, Visual Analysis - Tableau Software

Robert Kosara is a researcher in Tableau's Visual Analysis group. Before he joined Tableau in 2012, he was a professor of computer science at UNC Charlotte. Robert has created visualization techniques like parallel sets and performed research into the perceptual and cognitive basics of visualization. Recently, his research has focused on how to communicate data using tools from visualization, and how storytelling can be adapted to incorporate data, interaction, and visualization.

Robert received his M.Sc. and Ph.D. degrees in computer science from Vienna University of Technology (Vienna, Austria). His list of publications can be found online on his vanity website. He can be found on Twitter, Facebook, LinkedIn, Google+ and Google Scholar.