Browsing by Author "Dang, Tommy"
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Item The Gap between Visualization Research and Visualization Software in High-Performance Computing Center(The Eurographics Association, 2021) Dang, Tommy; Nguyen, Ngan; Hass, Jon; Li, Jie; Chen, Yong; Sill, Alan; Gillmann, Christina and Krone, Michael and Reina, Guido and Wischgoll, ThomasVisualizing and monitoring high-performance computing centers is a daunting task due to the systems' complex and dynamic nature. Moreover, different users may have different requirements and needs. For example, computer scientists carry out data analysis as batch jobs using various models, configurations, and parameters, and they often need to manage jobs. System administrators need to monitor and manage the system constantly. In this paper, we discuss the gap between visual monitoring research and practical applicability. We will start with the general requirements for managing high-performance computing centers and then share the experiences working with academic and industrial experts in this domain.Item ScagnosticsJS: Extended Scatterplot Visual Features for the Web(The Eurographics Association, 2020) Pham, Vung; Dang, Tommy; Wilkie, Alexander and Banterle, FrancescoScagnostics is a set of features that characterizes the data distribution in a scatterplot. These visual features have been used in various applications to detect unusual correlations of bivariate data. However, there is no formally published implementation for 3D or higher. This project aims to provide the Scagnostics implementation in JavaScript, called ScagnosticsJS, and also extend these measures for higher dimensional scattered points. We also present a Scagnostics exploration webpage, which makes the underlying algorithms transparent to users.Item WordStream: Interactive Visualization for Topic Evolution(The Eurographics Association, 2019) Dang, Tommy; Nguyen, Huyen N.; Pham, Vung; Johansson, Jimmy and Sadlo, Filip and Marai, G. ElisabetaThis paper introduces WordStream, an interactive visual tool for the demonstration of topic evolution. Our approach utilizes the two popular techniques. Word clouds are designed to give an engaging visualization of text via font sizes and colors, while stacked graphs are a common method for visualizing topic evolution. In particular, WordStream emphasizes essential terms chronologically and spatially. To show the usefulness of WordStream, we demonstrate its applications on various data sets, including the Huffington Post and IEEE VIS publications.