Difference between revisions of "About"
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==Motivation== | ==Motivation== | ||
| − | + | <p><span style="font-size: 11pt; font-family: Arial; color: #000000; background-color: transparent; font-weight: 400; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">Network patterns can reveal very interesting insights but it is very difficult to implement with off-the-shelf software tools such as Tableau®. Gephi®, an open-source and free software is one of the leading tools to visualise network graphs. But, in order to make our findings easily accessible to everyone without any installation of any tools at their end, we propose the usage of the recently introduced </span><em><span style="font-size: 11pt; font-family: Arial; color: #000000; background-color: transparent; font-weight: 400; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;">ggraph</span></em><span style="font-size: 11pt; font-family: Arial; color: #000000; background-color: transparent; font-weight: 400; font-variant: normal; text-decoration: none; vertical-align: baseline; white-space: pre-wrap;"> package from R. Besides bringing the same kind of flexibility offered by a commercial tool, it offers an extension on the well-acclaimed ggplot2 package in R. Built specifically for supporting relational data structures such as networks, graphs and trees, the API provides a self-contained set of facets and customisations, enhancing the quality of visualisations. </span></p> | |
==Practical use cases== | ==Practical use cases== | ||
Revision as of 14:55, 4 August 2017
Group1: Unlocking insights from the VAST Challenge 2017
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Abstract
The project aims to illustrate the power of visual analytics to highlight patterns vehicles show when traversing through various traffic corridors. By linking the information captured by RFID tags when vehicles move through checkpoints, an interactive application is designed which will help to unravel insights such as frequently travelled corridors, preferred routes amongst vehicles, traffic density, etc. The application will be primarily developed using R, and specifically the versatile ggraph package, which helps to develop powerful network visualisations.
Motivation
Network patterns can reveal very interesting insights but it is very difficult to implement with off-the-shelf software tools such as Tableau®. Gephi®, an open-source and free software is one of the leading tools to visualise network graphs. But, in order to make our findings easily accessible to everyone without any installation of any tools at their end, we propose the usage of the recently introduced ggraph package from R. Besides bringing the same kind of flexibility offered by a commercial tool, it offers an extension on the well-acclaimed ggplot2 package in R. Built specifically for supporting relational data structures such as networks, graphs and trees, the API provides a self-contained set of facets and customisations, enhancing the quality of visualisations.
Practical use cases
- Traffic planning.
- Systems such as Singapore ERP.
- Implementing diversions during peak periods.
