Track: Digital Media: Content and Communication
Minitrack: Visual analytics in the context of the organization

Visual Analytics is an inherently interdisciplinary research approach to information systems. It combines the scientific investigation of information processing in human-computer cognitive systems with the design and implementation of interactive visualization interfaces for difficult analytic tasks. Visualized data may be uncertain in fact, relevance, and location in space and time, and may be processed with statistical, mathematical models or AI in partnership with the human analyst. The results of VA research include not only new technologies, but also new ways of integrating technology in the organization, training analysts and evaluating the overall success of the analytic process.

Visual Analytics was defined as “ the science of analytical reasoning facilitated by interactive visual interfaces”. Data and information visualization have long been used to study scientific phenomena, analyze data, and to explore large amounts of multivariate data. In contrast to computation alone, visualization can harness the human mind’s innate “visual intelligence” to gain novel insights into situations characterized by complex data that may contain uncertainty in fact, relevance, location in space and position in time. While methods for creating graphical visualizations are well understood, visual analytics (VA) seeks to directly address the process of human reasoning with interactive visualizations. It does so by combining the scientific
investigation of human perception, cognition and interaction with information with advanced computation, mathematics and statistical analysis methods.

Formed in response to the vast amounts of data that can potentially inform human decision making across a broad range of activities, VA extends visualization research to take a scientific approach to the investigation of cognitive processing by human-computer systems in the context of organizations. Empirical methods range from social sciences approaches to organizational behavior in technology-enabled organizations to perceptual studies of individuals using interactive visualization environments to understand complex datasets. In parallel, technology
developers work to develop new algorithms for acquiring and processing data and new approaches to displaying it graphically for human understanding and interaction. This interplay between an emerging empirical science of cognitive systems and advanced graphical, computational, mathematical and statistical analysis methods form the basis for this new interdisciplinary field.

Visual Analytics research has received substantial funding from the US Department of Homeland Security through its National and Regional Visualization and Analytics Centers, with a follow-on Center of Excellence in Visual Analytics to come. The US National Science Foundation has the Foundations of Data and Visual Analytics program, and a new European Union7th Framework European Coordination Action “VisMaster” focuses on Visual Analytics. Other efforts include a Deutsche Forschungsgemeinschaft Priority Program "Scalable Visual Analytics".

VA applies to a broad range of situations where human expertise must be brought to bear on problems characterized by massive datasets and data that are uncertain in fact, relevance, location in space and position in time. Examples include environmental science and technologies, natural resources and energy, health and related life sciences, safety and security (aircraft safety, law enforcement, antiterrorism, disaster relief) and business processes.

The majority of previous VA events have emphasized the design of visual analytics technologies for applications in law enforcement, antiterrorism, and disaster relief. A few events have examined how human cognition and perception research can be applied to the design of VA systems. For this minitrack we hope to attract submissions that extend the areas of use to include a broader array of applications such as business intelligence, financial analysis, and other domains where interactive visualization systems may be used to improve human decision making. Research methods may include studies of visualization systems in the context of the organization (e.g. communication between analysts and policy-makers) as well as perceptual and cognitive aspects of individual and collaborative analysis using these systems. This includes communication between analysts and decision-makers. Educational programs that support
training of visual interaction designers are also welcome.

Minitrack Chair:

Brian Fisher
School of Interactive Arts and Technology
Simon Fraser University at Surrey
250-13450 102 Ave., Surrey BC V3T 0A3
Direct (SFU): 778-782-7554
Main (UBC): 604-822-8990
Email: bfisher@sfu.ca