#$treetCred

Portrait of $treetWork$ team as GovHack logo
Team Name: 
$treetwork$

Problem: How do you know the value of your public transport network to your community?

We made a tool for visualising and evaluate the socio-economic value of transport for all.

Check it out at http://streetcred.azurewebsites.net/ or the raw shiny app at http://139.59.252.21/shinyapp

Our rocking video is at https://youtu.be/uL6d70FKa0E

When we think about public transport services, we often think about things like fare prices, cost of services, the routes, and the on-time performance. These are all concerns for users and network managers, but they only provide part of the picture.

Unfortunately users’ additional needs may be overlooked, resulting in underused or inconvenient public transport services that make it difficult to travel from home to work, services and places of leisure. This especially presents challenges for disadvantaged groups.

For GovHack, we’ve chosen to look at Canberra as a small case study to investigate the benefits of integrating social and transport data, but the concept could be applied to other communities.

Our Story

This is the $treetWork$ team's first GovHack. We all share an interest in transport policy and seeking innovative ways to gain insights into how best to improve policy outcomes, and learning new processes to get there.

In $treetwork$, work is divided between two separate yet equally important groups: The analysts, who developed the app, and the non-analysts, who did everything else.

Check out our stories (and theme song) on the website - http://streetcred.azurewebsites.net/

Thanks to all the GovHack volunteers, data mentors and Canberra Grammar for hosting us! What a great event!

Used Datasets: 
Dataset Name: 
Job Services Australia Data
Publishing Organisation/Agency: 
Department of Employment
Jurisdiction of Data: 
Australian Government
How did you use this data in your entry?: 
To model disadvantaged users of transport network. To get better spatial granularity, the raw data has been weighted by the unemployed of the corresponding year and month in small area labour markets publication. (SALM)
Dataset Name: 
Small Area Labour Market
Publishing Organisation/Agency: 
Department of Employment
Jurisdiction of Data: 
Australian Government
How did you use this data in your entry?: 
Used as weight for job services australia data, and to model unemployed users of transport network
Dataset Name: 
3235.0 - Population by Age and Sex, Regions of Australia, 2014
Publishing Organisation/Agency: 
ABS
Jurisdiction of Data: 
Australian Government
How did you use this data in your entry?: 
To estimate total user population and population by age group
Dataset Name: 
Internet Vacancy Report
Publishing Organisation/Agency: 
Department of Employment
Jurisdiction of Data: 
Australian Government
How did you use this data in your entry?: 
To estimate vacancies. To get better spatial granularity, the raw data has been weighted by employment and occupation at place of work, using 2011 Census (ABS)
Dataset Name: 
Experimental Industry Estimates by Geographic Area
Publishing Organisation/Agency: 
Department of Industry, Innovation, and Science
Jurisdiction of Data: 
Australian Government
How did you use this data in your entry?: 
Estimate the value of economic activity spatially.
Dataset Name: 
SA3 Region Innovation Data 2009-15
Publishing Organisation/Agency: 
Department of Industry, Innovation and Science
Jurisdiction of Data: 
Australian Government
How did you use this data in your entry?: 
To estimate innovation spatially. For extra granularity, we weighted this to industry of employment at place of work (2011 Census ABS)
Dataset Name: 
Census 2011 at place of work
Publishing Organisation/Agency: 
ABS
Jurisdiction of Data: 
Australian Government
How did you use this data in your entry?: 
We used it to weight other datasets and to estimate the location of jobs.
Dataset Name: 
ACTION Bus Service GTFS Feed (ACT)
Publishing Organisation/Agency: 
ACTION Bus Network
Jurisdiction of Data: 
ACT Government
How did you use this data in your entry?: 
We looked at the transit network in Canberra against other datasets to model underlying social dimensions. This puts the user in focus to consider to what extent public transport connects job seekers with employment.
Event Location: 
Canberra