Workshop report: Building Linked Data heatmaps with Clojurescript &

Still from a previous London 3D data viz project done with & for The Open Data Institute in 2013, here showing knife crime incidents by borough.
Heatmap of average London property price per borough (2013/14) shows clear bias of high-price areas. Important note: We only used a sample of ~23k transactions to save time during the workshop. The full dataset published at contains >200k transactions.
Alternative heatmap based on number of sales per borough in 2013/14. There were ~2x as many sales in the south-east (orange) than in other areas (dark blue).
Charts of individual property sales per borough in 2013/14, sorted by date. Note the clearly visible upward trend for most boroughs. Charts are generated for all 33 boroughs, with the remainder omitted here for space reasons.
Screenshot of the query editor and auto-generated visualization of the shown query’s structure (courtesy and Graphviz on the server, editor uses CodeMirror)

Placing our data in a graph system not supporting these principles, will still give us potentially more flexible query capabilities locally, but will not automatically solve the old questions of how to easily combine knowledge from multiple sources or how to provide our own data in a semantically, interoperable format to others.

The Linked Open Data cloud as of 2014, an overview of interlinked open data sets describing over 8 billion resources
The readme for the LD module contains several examples how to interact with the server via HTTP.
brew install graphviz
Dynamically generated 3D meshes rendered in SVG with different (composable) software shaders
Blender’s Suzanne imported as STL and rendered in SVG with Phong sofware shader
Example gradient presets
Heatmap based on average sale price per borough
Heatmap based on number of sales per borough, same color preset as above. Dark green lowest, cyan highest numbers.
Using a linear scale y-axis is a bad choice for this data due to extreme price fluctuations in some boroughs (e.g. outliers like Kensington’s 27.9 million or Lambeth’s 7 million property sales cause havok)
The same data for the same boroughs mapped using a logarithmic scale
And once more using line chart with gradient
47k airports (magenta = IATA, cyan = non-IATA)



Computational design, data, TypeScript, Clojure/script, C

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