What Shakespeare Taught Us About Data Science and Visualization

In this talk, I will discuss some of the lessons we have learned from a collaboration between computer scientists and literature scholars. Our project sought to help scholars use data science methods to study historical literature at unprecedented scale.
In developing data-centric approaches to English literature of the Early Modern period (roughly 1470-1700, including Shakespeare), we gained a different understanding of data science.
The unique nature of the collaboration highlighted that working with data is a process with many stages, and that different users have different needs.
The project provided an opportunity for us to develop and test our ideas about tools for data analysis and visualization.
This talk will provide an overview of the project, and use the project as motivation for some of our recent results in understanding the data science process and providing data analysis and visualization tools.

Bio

Michael Gleicher is a Professor in the Department of Computer Sciences at the University of Wisconsin, Madison. Prof. Gleicher is founder of the Department’s Visual Computing Group.
His research interests span the range of visual computing, including data visualization, robotics, image and video processing tools, virtual reality, and character animation. His current foci are human data interaction and human robot interaction.
Prior to joining the university, Prof. Gleicher was a researcher at The Autodesk Vision Technology Center and in Apple Computer’s Advanced Technology Group.
He earned his Ph. D. in Computer Science from Carnegie Mellon University, and holds a B.S.E. in Electrical Engineering from Duke University.
In 2013-2014, he was a visiting researcher at INRIA Rhone-Alpes. Prof. Gleicher is an ACM Distinguished Scientist.

To get more info visit: http://pages.cs.wisc.edu/~gleicher/