Visual analytics in context: Theory into practice

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Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces. It is an evolving multidisciplinary field developed to help people derive insights from massive, dynamic, ambiguous, and often conflicting data. Visual analytics takes advantage of the visual intelligence and cognitive capabilities unique to human analysts, coupled with interactive, exploratory, and visualisation software tools. The primary scientific and technical objectives of the project are to better understand the nature and use of visual analytics systems and how they can be effectively applied to various industries working with large, complex date sets. The project will focus on three research directions by following a path from theory, to learning, to practice and deployment. First, we will conduct basic research on human visual capabilities relevant to information visualisation and visual analysis. Results of these investigations will establish theory relevant to how humans should design and use such systems, leading to enhanced designs using more effective visualizations. Next, we will develop a challenging learning environment where university students and industry employees can learn about visual analytics from experienced student mentors by using available visual analytics tools to explore real problems using real data sets. Finally, we will apply visual analytics techniques and tools to make visual sense of financial records. Guiding research questions include: how to apply visual analytics to support financial risk analysis and decision-making, how to analyse archival data, and how to conceptualize and analyse risk in the information assurance domain? Several benefits accrue as a result of this project. It will contribute to the advancement of Canada as a leader in visual analytics research, learning and deployment. The project involves a team of highly qualified students and researchers who will be trained in this promising and innovative new area of research. Upon completion, our industrial partners can use their new knowledge and procedures on their proprietary data, likely employing the unique skill sets acquired by the students and researchers involved in this project.