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Charles D. Stolper
Researcher at Georgia Institute of Technology
Publications - 15
Citations - 646
Charles D. Stolper is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Data visualization & Information visualization. The author has an hindex of 9, co-authored 15 publications receiving 473 citations. Previous affiliations of Charles D. Stolper include Microsoft & Southwestern University.
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Progressive Visual Analytics: User-Driven Visual Exploration of In-Progress Analytics
TL;DR: This paper presents an alternative workflow, progressive visual analytics, which enables an analyst to inspect partial results of an algorithm as they become available and interact with the algorithm to prioritize subspaces of interest.
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Vispubdata.org: A Metadata Collection About IEEE Visualization (VIS) Publications
Petra Isenberg,Florian Heimerl,Steffen Koch,Tobias Isenberg,Panpan Xu,Charles D. Stolper,Michael Sedlmair,Jian Chen,Torsten Möller,John Stasko +9 more
TL;DR: A dataset with information about every paper that has appeared at the IEEE Visualization set of conferences: InfoVis, SciVis, VAST, and Vis is created and made available to all.
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State of the Art of Sports Data Visualization
Charles Perin,Charles Perin,Romain Vuillemot,Charles D. Stolper,John Stasko,Jo Wood,Sheelagh Carpendale +6 more
TL;DR: This report analyzes current research contributions through the lens of three categories of sports data: box score data, tracking data, and meta‐data (data about the sport and its participants but not necessarily a given game), identifying critical research gaps and valuable opportunities for the visualization community.
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SnapShot: Visualization to Propel Ice Hockey Analytics
TL;DR: Working closely with professional ice hockey analysts, SnapShot is designed and built, a system to integrate visualization into the hockey intelligence gathering process, and a technique, the radial heat map is introduced.
Emerging and Recurring Data-Driven Storytelling Techniques: Analysis of a Curated Collection of Recent Stories
TL;DR: This work advances the study of narrative visualization through an analysis of a curated collection of recent data-driven stories shared on the web, and presents a set of techniques being employed in these examples, organized under four high-level categories that help authors to tell stories in creative ways.