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Dr. Christopher Healey Associate Professor of Computer Science NC State University |
This module will address the growing interest in visualization and visual analytics, the process of analyzing data through images. The ability to generate and store massive amounts of information has produced a critical need for this capability. Visual analytics involves more than simple picture building. Issues of data management, human perception, assisted design, visual aesthetics, practical aspects of the data to be displayed, and the analyst’s needs—all are important and need to be considered when we decide how to visualize data. An introduction to visualization and visual analytics will be provided, with emphasis on government agencies and industrial partners who are strongly encouraging research in these areas. Topics include: managing large datasets; harnessing the strengths of our human visual system; helping non-experts build high quality visualizations; how aesthetics can improve information retention; and ways to infer and dynamically update a visualization to fit an analyst’s changing interests. The module will conclude with case studies that demonstrate how theoretical results can be applied in a real-world context. These lectures will provide students with a comprehensive overview of many important issues in visualization and visual analytics. They will also see how state-of-the-art techniques can be applied to visualize data for real users in a number of different problem domains.
Major topics:
- Visualization and visual analytics: an introduction
- Managing large datasets
- The role of human perception in information presentation
- Assisted visualization design
- The power of aesthetics for knowledge retention
- Implicit tracking of viewer’s interests
- Case study I: On-line analytic processing (OLAP) data cubes
- Case study II: Recommender systems