Difference between revisions of "Arisaig Final Progress"
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# Interactivity of Multi-Linked Views | # Interactivity of Multi-Linked Views | ||
# Context Provision | # Context Provision | ||
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| + | ''Visual Representation of Spatial Data''<br> | ||
| + | The spatial data provides the opportunity to provide representation of how geographical proximities could have inter-dependency that would give the investors better insights for decision-making. This opportunity creates the problem of how to represent information such that it is still comprehensive to budding analysts/investors. In order to cater to this need, the project implemented Choropleth for the visualization of spatial data. <br><br> | ||
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| + | Choropleth provides an overall map view to see the performance of the various countries and regions with respect to a certain variable at question. The limitation is that Choropleth which showcases the countries rankings through the use of color intensity is only able to showcase one variable at a time (univariate). In order to improve the functional use of Choropleth in representation of the such data, it could be done through the integration of zoomable user interface (ZUI). It is developed to allow user to zoom in on selected region for a focused view of the visualisation. In addition, the interactivity of Choropleth would be better with the graph being responsive to user clicks and selections on the map, allowing user to view information of only “what that is of interest”. All in all, these designs would help supplement the analytical value of the Choropleth map. | ||
Revision as of 16:42, 20 April 2015
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Home | Project Proposal | Project Management | Project Progress | Project Final Progress | Final Deliverable |
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Data Understanding & Representation
As mentioned of the nature of the project, it involves the use of multi-dimensional data, the following are the main categories that the project uses:
- Spatial (geographical) data
- Temporal (time-series) data
This creates challenges in terms of understanding how the various data interact and work together as well as the representations of the findings of the patterns and relationships within the data. In the following parts, the main challenges addressed in this thesis are:
- Visual Representation of Spatial Data
- Visual Representation of Temporal Data
- Visual Representation of High Dimensional Data
- Interactivity of Multi-Linked Views
- Context Provision
Visual Representation of Spatial Data
The spatial data provides the opportunity to provide representation of how geographical proximities could have inter-dependency that would give the investors better insights for decision-making. This opportunity creates the problem of how to represent information such that it is still comprehensive to budding analysts/investors. In order to cater to this need, the project implemented Choropleth for the visualization of spatial data.
Choropleth provides an overall map view to see the performance of the various countries and regions with respect to a certain variable at question. The limitation is that Choropleth which showcases the countries rankings through the use of color intensity is only able to showcase one variable at a time (univariate). In order to improve the functional use of Choropleth in representation of the such data, it could be done through the integration of zoomable user interface (ZUI). It is developed to allow user to zoom in on selected region for a focused view of the visualisation. In addition, the interactivity of Choropleth would be better with the graph being responsive to user clicks and selections on the map, allowing user to view information of only “what that is of interest”. All in all, these designs would help supplement the analytical value of the Choropleth map.
Here is the report
