Spatio-temporal datasets like sensor-data or floating car data can be rather overwhelming because they quickly get in the order of billions of records.
In this talk I show how we made billions of floating car data entries into a workable datastream that outputs visually attractive and useful maps and graphs over a routable network. I will start by summarizing the relatively new OS clickhouse database and how this column store helps in dealing with massive temporal datasets. Next I explain how we set up the pipeline with postgres/gis, pgrouting and R in order to create analysis in seconds and share some interesting results that you can get from these large trafficdatasets.
The talk will be relatively code-focused (mainly SQL and R) but also show some ind-depth analyses of car data.

More open pointcloud data is released every year and with it there is an increasing request for automatically generated large scale digital maquettes that can be used in city-planning, environmental modelling and 3D data-analysis. We will show how we use a pipeline of OS software that goes from pointclouds and cadastral data to a full scale 3D maquette of your country. Processing happens mostly in postgres and takes typically a couple of minutes per square km.

Included in the talk is: * introduction of some python-scripts for pointcloud-processing * adoption of procedural language in postgres * advanced use of postgis (voronoi, sfcgal etc) * generating 3D tiles * styling a maquette in cesium

The presentation will be fast paced and includes a range of technical details but should be understandable for the average person. It includes code examples and live demo's. In the end you will have an understanding of available software (both new and existing), do's and don'ts in generating 3D data with OSS and contemplations on how to use a digital 3D maquette.

Mapbox GL JS is a powerful JavaScript library that uses WebGL to render interactive maps from vector tiles and other sources. Mapbox has recently added custom layers to its set of allowed layer types. The custom layer allows developers to render custom data while directly using the the WebGL render engine.

We have implemented mapbox-gl custom layers for rendering 3D tiles and point cloud data. This enables the already feature rich Mapbox rendering engine to be combined with web-visualization of true geographic 3D data directly from OGC formats. An advantage of this is that you can use the mapbox navigation and base-layer rendering while at the same time complex 3D objects directly to your web browser. in a way similar to vectortiles in 2D space.

In this talk we will demonstrate an implementation of a 3D Tiles viewer as a Mapbox GL JS custom layer. WebGL rendering is implemented using three.js. This addition enables you to add a 3D-tiles layer with true 3D objects on top of your existing mapbox implementation just as easy as you would be adding a vector-tile service.

We will discuss some technical issues we have encountered, give examples on how you can use it and show an extensive demonstration of what you can do with it.