Government dashboards and open data.
summary
Details on what was built and what actually works: Django backend with an API serving metadata-driven widgets to pure JavaScript front ends, support for views by location/frequency/theme, automated loaders that pull CSV JSON XML or scrape when needed, refresh intervals and access control. Concrete problems and numbers: inconsistent LGA identifiers and misspellings, multiple divergent population projection sets, ZIPped XLSX chaos, broken JSON characters, reluctance to publish provisional figures. Prototypes exist and some deployments run in production.
AI-written summary · about
chapters (14)
- 0:00Introduction
- 0:40Open data
- 5:25New South Wales government dashboards
- 6:00Architecture
- 7:28Views
- 8:50Widgets
- 10:30Statistics
- 11:54Types of widgets
- 13:35API methods
- 14:13Widget definition
- 16:30Obstacles
- 17:22Examples
- 19:13Accuracy
- 20:16Future plans
related talks
22mGovernment dashboards and open data.
43mBehind the Scenes at Gapminder: A Story about Data and Visualizations
34mLiberation and modernization of government legacy data using Django
30mMeta-Dashboards: Accelerating Geospatial Web Apps Creation with Voilà
29mUsing Dash by Plotly for Interactive Visualisation of Crime Data
24mData science, apps and civic responsibility
27mLessons Learned Building Our Own Dashboard Solution
33mData Science & Data Visualization in Python