This Brown Bag reviews papers and posters presented by GT researchers during the InfoVis Conference and the Visual Analytics Symposium at IEEE VisWeek, October 12-16 in Atlantic City. The following articles will be presented:

TITLE: SellTrend: Inter-Attribute Visual Analysis of Temporal Transaction Data (InfoVis full paper, Honorable Mention Best Paper)
AUTHORS: Zhicheng Liu, John Stasko, Timothy Sullivan

ABSTRACT: We present a case study of our experience designing SellTrend, a visualization system for analyzing airline travel purchase requests. The relevant transaction data can be characterized as multi-variate temporal and categorical event sequences, and the chief problem addressed is how to help company analysts identify complex combinations of transaction attributes that contribute to failed purchase requests. SellTrend combines a diverse set of techniques ranging from time series visualization to faceted browsing and historical trend analysis in order to help analysts make sense of the data. We believe that the combination of views and interaction capabilities in SellTrend provides an innovative approach to this problem and to other similar types of multivariate, temporally-driven transaction data analysis. Initial feedback from company analysts confirms the utility and benefits of the system.

TITLE: Evaluating Visual Analytics Systems for Investigative Analysis: Deriving Design Principles from a Case Study (VAST full paper)
AUTHORS: Youn-ah Kang, Carsten Gorg, John Stasko

ABSTRACT: Despite the growing number of systems providing visual analytic support for investigative analysis, few empirical studies of the potential benefits of such systems have been conducted, particularly controlled, comparative evaluations. Determining how such systems foster insight and sensemaking is important for their continued growth and study, however. Furthermore, studies that identify how people use such systems and why they benefit (or not) can help inform the design of new systems in this area. We conducted an evaluation of the visual analytics system Jigsaw employed in a small investigative sensemaking exercise, and we compared its use to three other more traditional methods of analysis. Sixteen participants performed a simulated intelligence analysis task under one of the four conditions. Experimental results suggest that Jigsaw assisted participants to analyze the data and identify an embedded threat. We describe different analysis strategies used by study participants and how computational support (or the lack thereof) influenced the strategies. We then illustrate several characteristics of the sensemaking process identified in the study and provide design implications for investigative analysis tools based thereon. We conclude with recommendations for metrics and techniques for evaluating other visual analytics investigative analysis tools.
TITLE: Two-stage Framework for Visualization of Clustered High Dimensional Data (VAST full paper)
AUTHORS: Jaegul Choo, Shawn Bohn, Haesun Park

ABSTRACT: In this paper, we discuss dimension reduction methods for 2D visualization of high dimensional clustered data. We propose a twostage framework for visualizing such data based on dimension reduction methods. In the first stage, we obtain the reduced dimensional data by applying a supervised dimension reduction method such as linear discriminant analysis which preserves the original cluster structure in terms of its criteria. The resulting optimal reduced dimension depends on the optimization criteria and is often larger than 2. In the second stage, the dimension is further reduced to 2 for visualization purposes by another dimension reduction method such as principal component analysis. The role of the second-stage is to minimize the loss of information due to reducing the dimension all the way to 2. Using this framework, we propose several two-stage methods, and present their theoretical characteristics as well as experimental comparisons on both artificial and real-world text data sets.

TITLE: Social Visualization for Micro-Blogging Analysis (InfoVis poster)
AUTHORS: Tanyoung Kim, Hee Young Jeong, Yee Chieh Chew, Matthew Bonner, John Stasko

TITLE: Interactive Visualization of Ecosystem Change for Public Education (InfoVis poster)
AUTHORS: Tanyoung Kim, Hwajung Hong, Brian Magerko

TITLE: Perspectives on Time: Enhancing Utility with Flexibility (InfoVis poster)
AUTHORS: Peter Kinnaird, John Stasko

TITLE: Connect to Congress (InfoVis poster)
AUTHORS: by Peter Kinnaird, Hafez Rouzati, Xin Sun