GovHack 2015

This project started out as one of several products entered by team Bangers n’ Mashup for their project yes we CKAN at the GovHack 2015:


  • The timeseries explorer was created before the GovHack and serves only as an illustration of an interactive, data-driven application to bridge the gap between raw data and meaningful visualisation.
  • The datacats CKAN install was created after the GovHack, as a critical bug with a Docker version rendered datacats unusable during the contest, but was fixed one day afterwards.
  • This documentation (submitted `version`_) was hosted on after the contest and is under active development.
  • The video was modified after the contest: the audio was shifted by ca. 200ms to counter the audio lag introduced by the hosting on, and a few words have been edited in the introductory slides. However, the general content and message have not been altered.


The installation documented in Alternatives demonstrates the most low-level hands-on way of installing a CKAN data catalogue, an installation from source. There are several quicker, but less customisable ways:

Our approach hopes to demonstrate our lessons learnt:

  • It is possible to setup and host a working CKAN from scratch within a day.
  • A source install, while not advisable for production use, allows to fix bugs and add new functionality, and contribute these improvements back to the CKAN community.
  • We demonstrate how to scale the install to include and host other useful servers like R Studio Desktop and R Shiny Server.
  • We include a scalable way to host a multi-tenant CKAN install following the WA Department of Parks and Wildlife’s working multi-tenant setup. The description of the multi-tenant install was created before the GovHack and is not to be considered for judging. However, we hope it provides value for real-world use past the GovHack event.

Future directions

This repository will be updated as work progresses on the CKAN installation. We plan to include installation examples using Datacats (plus Docker-based installs of R Studio Server and R Shiny Server) as well as Datashades’ CKAN Galvanize.