Advances in browser and mobile technologies have made the visualization and interaction of data on web a viable alternative to traditional tools used to visually explore data. Panelists will discuss the current state of web data visualization, as well as novel approaches made possible by recent advances.
Kevin visualizes data and makes statistical interfaces on the web. Before Clojure, he wrote machine learning and analytics tools in R and Scala. In 2010 he wrote a thesis on protein structure, for which Reed College inexplicably awarded him a physics degree. Kevin lives in Portland, Oregon, and spends as much time rock climbing as he does in the REPL.
Kim Rees is a founding partner of Periscopic: http://www.periscopic.com, an award-winning information visualization firm. Their work has been featured in the MOMA as well as several online and print publications, including CommArts’ Interactive Annual, The Information Design Sourcebook, Adobe Success Stories, CommArts Insights, Infosthetics.com, FlowingData.com, and numerous websites, blogs, and regional media outlets. Periscopic’s body of work was recently nominated for the Cooper-Hewitt National Design Awards.
Kim is a prominent individual in the information visualization community. She has published papers in Parsons Journal of Information Mapping, was an award winner in the VAST 2010 Challenge, and is a guest blogger for Infosthetics.com. Kim has been featured on CommArts Insights and has presented at several industry events including Strata, the Tableau Software Conference, AIGA SHIFT, WebVisions, CERF Biennial Conference, and Portland Data Visualization, among others. Recently she has also been an advisor on an upcoming documentary film and is the Technical Editor for Visualize This by Nathan Yau. Kim received her BA in Computer Science from New York University.
Hadley Wickham is an Assistant Professor and the Dobelman Family Junior Chair in Statistics at Rice University. He is an active member of the R community, has written and contributed to over 30 R packages, and won the John Chambers Award for Statistical Computing for his work developing tools for data reshaping and visualisation. His research focusses on how to make data analysis better, faster and easier, with a particular emphasis on the use of visualisation to better understand data and models.
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