Chatbots are the Future
How can we effectively engage with open data using Chatbots?
Go to Challenge | 11 teams have entered this challenge.
Team Name:
Six to Fix
Team Members:
Project Glad You Bot It Up
Project Info
Team Name
Six to Fix
Team Members
2 members with unpublished profiles.
Project Description
Everyone's life is always busy. You have to take care of your family, your finances, your jobs and relationships. The last thing you want to worry about is contacting agencies for help and find out that you have to wait on the phone line to even talk to someone to solve your issue.
Our solution includes a location optimisation tool by heat mapping the traffic of government facilities, such as ATO Tax help centers, across Australia and using conversational AI to provide tailored responses to end users based on their preferences.
Data Story
Data Sources:
1. Gov Hack 2018
URL: https://data.gov.au/dataset/govhackato/resource/f3bcbd38-b3e9-4a27-8729-2314f05a6ae4
2. Download Austalian Postcodes
URL: https://www.matthewproctor.com/australian_postcodes
Technologies:
1. Jupyter Notebook 5.0.0 & Python 2.7.13 for Data Wrangling
2. Tableau 10.5.2 for Data Visualisation
3. Chatbot - Chirpy AI Chatbot Platform - https://getchirpy.ai
Github Link: https://github.com/DnyaneshDesai/GovHack2018
Chatbot Links:
- Individual: http://bit.ly/chirpy-individual
- Volunteer: http://bit.ly/chirpy-volunteer
Data Collection Spreadsheet: https://docs.google.com/spreadsheets/d/1ulH5O53HgduCizTwS4-bdxSAwHMlPgxB-VynaPRGwZI/edit?usp=sharing
Github File Information:
GovHack2018DataWranglingPythonNotebook.ipynb : File that contains entire data wrangling code
atoabsgovhack2018.xlsx: Initial dataset file
australianpostcodes.csv: Initial dataset file
NSWDataforExploration.csv: Output file that contains details of 2016 tax offices
NSWDataforallyearsExploration.csv: Output file that contains details of 2006,2011 & 2016 tax offices
Visualization1.twb: Tableau file for visualisation
Tableau Dashboard Link:
https://public.tableau.com/profile/dnyanesh.desai#!/vizhome/Visualization_1_7/Dashboard1
Tableau Dashboard Information:
1. Tax Payer Density Vs No. Of Tax Centres Map describes the density of tax payers per postcode along with the number of tax help centres in the particular postcode.
2. Individuals served by each Tax Centre Map helps to see how many number of individuals are served by each Tax centre. This helps to identify the load on each centre.
3. Data Table for Postcode Information This data table displays the history information for postcode selected by the user.
Overall the visualisation allows the government to decide the location of the new tax help centre considering the growth of count of tax payers & the load on the current tax centres in any postcode.
Team DataSets
Download Austalian Postcodes
Description of Use Used the location coordinates to plot the tax centres on the maps of New South Wales (NSW)
Gov Hack 2018
Description of Use Used the file to get the trends of tax payers and the density of tax payers in particular postcode
Challenge Entries
Data4Good
How can open data be used to make a social impact, contributing to the betterment of society? How can we improve prospects for children, and education, using open data? What sort of impact can be made on homelessness, mental health outcomes, or the environment, using open data?
Go to Challenge | 19 teams have entered this challenge.
What do you want from government data challenge?
How should NSW government best provide data to the developer community? Show how our data can be made more usable for developers. What quality or format or standardisation issues does government need to fix or to consider? What developer community needs does the government need to support better?
Go to Challenge | 13 teams have entered this challenge.
The Friendly ATO
How can the ATO use artificial intelligence or machine learning to better understand and develop ways to engage with our clients?
Go to Challenge | 15 teams have entered this challenge.
Spatial data challenge
How can spatial data be leveraged to provide the best community outcome? How can this mapping data be used to deliver value to the people of NSW?
Go to Challenge | 14 teams have entered this challenge.
Bounty: Tax Help Centers
Looking at how the ATO could use artificial intelligence or machine learning to locate the best locations for Tax Help Centers
Go to Challenge | 21 teams have entered this challenge.
More than apps and maps: help government decide with data
How can we combine data to help government make their big and small decisions? Government makes decisions every day—with long term consequences such as the location of a school, or on a small scale such as the rostering of helpdesk staff.
Go to Challenge | 58 teams have entered this challenge.