Layering high-dimensional data is one of the three generic software methods that are the result of my innovative mathematical spaces and transformations. When talking about its benefits with a mathematician and programmer, the term ‘3D Diagrams’ was born – with the description of being ‘uncluttered’.
For I was using data from the London Air Quality Network which has been recording measurements of pollutants and weather conditions over 200 sites, but a lot of them have been closed.
Regarding the visualisation of the measurements recorded:
- a maximum of six sites can be plotted;
- a maximum of six pollutants or weather conditions per site can appear in a graph.
Excel is not limiting the amount of data, but produces a similarly ‘cluttered’ graph:
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| London Air Network | Excel |
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| Uncluttered ‘3D Diagram’ – with spatial and temporal dimensions as vertical ‘layers’ | ‘3D Diagram’ – with Layers Sorted – thanks to new Metrics |
The benefits:
- real ‘uncluttering’ occurs when the layers are sorted;
- any number of sites and pollutants can be visualised;
- new quantifications, i.e. ‘metrics’ can be derived.
To be able to monitor trends in an innovative way:
- weekly and 2-weekly data is visualised to ’embrace’ daily recordings
- the ‘visual space’ for even more ‘visual clarity’ will be improved in future versions.
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| Excel: NO (Nitron Oxide) recorded in Daily, Weekly and 2-Weekly intervals | ‘3D Diagram’ – with ample ‘visual space’ for more metric analysis |
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| Excel: NOX (Nitron Oxides) recorded in Daily, Weekly and 2-Weekly intervals | ‘3D Diagram’ – with ample ‘visual space’ for more metric analysis |
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| Excel: NOX2 (Nitron Dioxides) recorded in Daily, Weekly and 2-Weekly intervals | ‘3D Diagram’ – with ample ‘visual space’ for more metric analysis |
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