Data Visualization for query about preferred paths to favourite points of interest based on an abstracted local model for location aware Mobile devices

This internship proposes an abstract model, based on a local of the node where the users are located, instead of a global navigable map. This model is concerned about satisfying users’ transactional need to compare modes of transportation and the costs and outcome of each mode, rather than understanding contextual information about each POI (location). The research team proposes a model that is similar to the way ants find navigation routes. Study shows that ants follow routes that other ants follow. The research team believes, similarly humans, are more inclined to follow routes that are already taken and established, in other words, they follow other people’s footsteps. In this model, what users need is not a global view of space and its’ possibilities; but rather a local view of routes that are ratified and solidified based on trend following. In the course of the research, the team will build a prototype that represents their model, and assesses its usability in context. Several variables that are worthy of investigating in their evaluation of the model are cognitive understanding of the abstract model, ease and transactional speed of use, portability across various hardware platforms, and user’s subjective satisfaction in terms of way‐finding and developing a mental model of real spatial connectivity.

Faculty Supervisor:

Dr. Brian Fisher


Melahat Hosseini


IOTO International Inc.


Interactive arts and technology


Information and communications technologies


Simon Fraser University



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