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To view the Spring 2024 Academic Calendar, go to www.sfu.ca/students/calendar/2024/spring.html.
Visual Analytics
The graduate certificate in visual analytics (VA) is an interdisciplinary graduate program consisting of technology and theory courses along with courses on applications of this new field from the Schools of Interactive Arts and Technology and Computing Science, from the Faculty of Business, Faculty of Education, and the Faculty of Communication, Art and Technology.
The graduate certificate combines the four key aspects of visual analytics: cognition, technology, society, and integration. Integration is realized in a practical sense through completion of a substantial research project using visual analytics methods, typically the student’s thesis work or a separate significant research project. This falls under the jurisdiction of the student’s department or school, and is thus outside of the scope of requirements for the VA graduate certificate. Support for integration is provided by the VA graduate certificate program however, through facilitating participation of the SIAT Graduate Program Committee members on supervisory committees and through the Visual Analytics seminar series.
The program is offered at the Burnaby and Surrey campuses.
For further information, visit http://www.sfu.ca/siat/graduate.html.
Admission Requirements
Applicants must satisfy the University admission requirements as stated in the Graduate General Regulations 1.3 in the SFU Calendar. There is no direct entry to the VA graduate certificate. VA graduate certificate students must be enrolled and in good standing in a graduate degree program at SFU, and must graduate in order to receive the graduate certificate. Qualified students should submit their registration information to the SIAT Graduate Program Committee as early as possible.
Program Requirements
This program consists of course work for a minimum of 12 units.
Students complete
Aims to be a research seminar on new methods, techniques and applications in Visual Analytics (VA), for exposure to diversity of VA research work and method, for fostering understanding of VA disciplinary commonalities and differences. Graded on a satisfactory/unsatisfactory basis. Prerequisite: Registered graduate students from the School of Interactive Arts and Technology, or with permission of the instructor.
and three additional courses that in total cover the following areas. Course selection must be approved by the SIAT Graduate Program Committee.
Cognitive Processes
Courses fulfilling this requirement must cover the cognitive processes that underlie analytic practice and human problem-solving. Course work may include
Design principles for multimedia learning are derived from the theories and research of cognitive science. Topics include: tutorial interactions, history of adaptive learning systems, adapting to individual differences, dialogues with teachers (and other agents), problem solving and cognitive load, learning from multimedia, cognitive principles for document design, tools for self-regulated learning, intrinsic and situational motivation, simulations and self-regulated inquiry, inquiry with microworlds and cognitive tools, multimedia scenarios for anchored instruction.
Visual Analytics Technology
Courses fulfilling this requirement examine the creation, selection, and customization of information systems in the student's discipline or area of interest. This includes data processing and modeling as well as interactive visualization. Course work may include
An introduction to the theories and practices of managing information technology. Uses case studies to analyze complex situations and develop skills necessary to select, deploy and use information systems.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
| G100 |
Sharon Wallace |
TBD |
Advanced topics in data visualization. Topics covered may include principles of data representation, data presentation, data interaction, data physicalization, data and visualization literacy, data visualization and diversity, open data, and public personal data visualization. Students with credit for CMPT 878 or 775 may not take this course for further credit.
The concepts, theories and technology behind 3D representation and 3D geovisualization of complex spatial phenomena using emerging interactive, immersive and ubiquitous interface technologies. Combines geovisualization, geospatial interface research, geovirtual environments, GIScience, and spatial knowledge acquisition perspectives. Prerequisite: Enrolment in any graduate program plus permission of the instructor. Graduate students from other disciplines are welcome to take this course.
Provides a cognitive and computational framework for understanding and designing graphical and visual representations. Investigates several psychological and computational models of diagram processing, and explores diverse interactive graphical systems.
Social Systems
Courses fulfilling this requirement examine the impact of advanced data technology on individuals, organizations, and society in order to determine how it can best be designed and introduced to support social and collaborative processes. Course work may include
A seminar format will be used to discuss the concepts and frameworks essential to the effective management of information technology. Our focus will be on the strategic role that information systems play in organizations, their structure and components, and various perspectives on how to plan and manage this technology. Equivalent Courses: MBA621.
| Section | Instructor | Day/Time | Location |
|---|---|---|---|
| G100 |
Annamina Rieder |
TBD |
A study of the social theory of information technologies, examining issues affecting computer-mediated communication.
Examines the social environment of offenders through a criminal network perspective. Emphasizes how analyzing delinquency through the lens of networks can make theoretical and empirical contributions to the field.
Introduces the core values of interdisciplinary scholarship through engagement with history, theory and practice in the study of science, technology, society and culture. This course will be a reading-intensive, extended seminar style investigation of theoretical and historical references in science and technology studies and broader societal implications of technologies. Prerequisite: SIAT Graduate Student.
Use of quantitative methods of risk assessment and decision analysis to explicitly take uncertainty into account when making decisions in management of natural resources. Methods of quantifying uncertainty and the resulting risks. Examples from management of forests, wildlife, fisheries, water resources, energy, and toxic chemicals. Communicating information about uncertainties and the resulting risks to resource managers, the public, and scientists. Advantages and limitations of various quantitative methods. Includes computer laboratories. Prerequisite: Permission of instructor.
Subject to SIAT Graduate Program Committee approval, students may fulfill these requirements through other appropriate graduate courses at Simon Fraser University.
Course work must be selected from at least two academic units, with a maximum of two courses from the student’s home department.
Program Length
Students are expected to complete the program requirements within the normal completion time of their graduate degree.
Academic Requirements within the Graduate General Regulations
All graduate students must satisfy the academic requirements that are specified in the Graduate General Regulations, as well as the specific requirements for the program in which they are enrolled.