Visual Analytics

Visual Analytics is “the science of analytical reasoning facilitated by interactive visual interfaces”(Thomas and Cook, 2005). Areas as diverse as finance and business intelligence, education, transportation safety, freedom from crime and the threat of terrorism, public health, and environmental protection among others require the creation of information systems that support human cognitive processes such as learning and discovery, insight, creativity, reasoning and problem solving, coordination, and communication and that enable those innately human abilities to function at their best in information spaces that may include large volumes of data that are confusing, complex and uncertain.

These applications require technologies that support the blending of human cognitive abilities with computational processes. This in turn demands design methodologies that incorporate and advance a new translational cognitive science of human-information interaction. This new science must address research questions that emerge from field studies of “cognition in the wild’– at different stages of cognitive development, by aging and handicapped individuals, as well as by expert decision makers across a broad range of domains and situations. It must be precise enough to effectively guide technology builders, interaction designers, managers and trainers of a new generation of computationally-sophisticated decision makers.

Visual analysts use a wide variety of computer techniques and models to provide timely, defensible, and understandable assessments of complex situations and then communicate those assessments to policy and decision makers. Visual analytics provides computer-based tools that enable decision-makers to synthesize information and derive insight from changing and often conflicting data.

Visual Analytics Projects at MAGIC/SCIENCE Lab are here

Building VA in Canada

The proposed Canadian Network of Visualization and Analytics Centers (http://cnvac.ca) is based on a partnership between universities, the private sector and government agencies.

CNVAC will support collaboration between research centres that will better enable them to conduct VA research and train students to address the design, evaluation, and integration of VA technologies into knowledge work opportunities that span public and private sectors.

The program builds upon recognized Canadian expertise in the development, evaluation, and use of information technologies that support human decision-making. Researchers at Simon Fraser University and the University of British Columbia have a nucleus of expertise in all relevant areas, including: applied mathematics, computer graphic design, information visualization, cognitive science (especially visual cognition), human-centered information management and computer science. Other regions in Canada are well-positioned to build their own focused research and training programs that will insure that Canada maintains its position as a leader in this important new field.

Western VAC

CNVAC Centres will perform visual analytics research and develop university and graduate-level training programs. The initial phase for the Western VAC will be a focused research project between SFU and UBC , key industry partners (such as Boeing) and Canadian government agencies. We will focus on four key sectors, including manufacturing, finance, health and information communication technology (security). The development of the VA curriculum will be based on real-world experiences using large datasets and VA tools. University researchers and graduates will analyze, observe, and learn more about these datasets to “see” anomalies and patterns. The second phase will create a community of expert researchers and students capable of assessing and developing tools for a variety of domains.

Benefits to Canada, Canadian Industry and Government

This university-private sector collaboration will:

Perform research into visual analytic methods for analyzing complex maintainability, reliability, and safety data for large and complex systems using real data from Boeing. Ultimately, these techniques will be generalized to apply to a wide range of areas crucial to Canadian government and industry in the four focus sectors.

Perform research to identify new visual analytic techniques to help the specialist communicate analysis results to non-specialist decision makers.

Advance the science of visual analytics to develop a core competency for the design of new interactive technologies for decision support.

Train highly qualified Canadian personnel in the context of industry partner’s real-world situations, technologies and applications and from this develop a core VA curriculum.

These new visual analytic approaches will accelerate Canadian competitiveness.