The name of the software is a reflection of the process of human thought: to think, to shake up. It was written as part of my doctoral work in Computer Science at Simon Fraser University.
This software is based on:
- django 1.8.5
- python 3.5
It expects that gnuplot is available at /usr/local/bin/gnuplot
A new paradigm for exploration in computer-aided visualization
This dissertation examines how the computer can aid the creative human endeavour which is data visualization. That computers now critically aid many fields is apparent, as is evidenced by the breadth of contemporary research on this topic.
Indeed, computers have contributed widely to the whole area of data comprehension, both in performing extensive computations and in producing visual representations of the results. Computers originally aided mathematicians who could both write the instructions necessary to direct the computer and interpret the resulting numbers. Even though modern computers include advanced graphical capabilities, many issues of access still remain: the users of data visualization software systems may not be experts in any computer-related field, yet they want to see visual representations of their data which allow them insight into their problems. For example, today’s mathematicians who are generally expert in exploiting computational opportunities for experimentation may lack similar experience in opportunities for visual exploration.
Of particular concern is how a computer-aided visualization tool can be designed to support the user’s goal of obtaining insight. There are many visual representations for a given set of data, and different people may obtain insight from different visual representations. Selection of the “best” one for an individual can be exceedingly difficult, as the sheer number of possible representations may be staggering. Current software designs either recognize the possibility of overwhelming the individual and therefore employ some means of restricting the choices that the user is allowed to make, or the designs focus on providing only the raw materials necessary for constructing the representations, leaving the user unrestricted but potentially unaided in searching out the desired representation.
The novel approach presented in this dissertation adapts a genetic algorithm to provide a means for an individual to search alternative visual representations in a systematic and manageable way. Any visual representation is a combination of elements, each selected from a different component. This approach encourages the individual’s creativity without restricting available choices, and leaves the task of bookkeeping to the computer.
A computer-aided visualization system which is driven by the unique preferences of each user has been developed. The efficacy of this system, cogito, is demonstrated through a software user study. From an initial specification of components and elements, the system provides a wide variety of visual representations. From within this range of available visual representations, the user pursues the goal of achieving insight by applying personal criteria for effectiveness to the iterative selection and evaluation of candidate representations.