Team Name:
Team Placeholder
Team Members:
Team Placeholder
Placeholder combines multiple data sets, NSW spatial APIs, simple natural language processing and both web-based and physical visualization to help the ATO make better make decisions about where services to its more vulnerable clients should be focused in the future.
For our physical visualization, see below:
Placeholder helps the ATO target their tax help program by combining the following:
1. income tax return data from the GovhackATO dataset to target areas with the most eligible clients i.e. low income and net capital gain areas;
2. ABS demographic data from the GovhackATO dataset and geo-locations of retirement villages and technical schools from NSW spatial APIs to target vulnerable students and seniors;
3. personal insolvency data on tax related insolvencies from the AFSA non-compliance in personal insolvency dataset to identify key under-served areas; and
4. flood zoning data from SEED Environmental Planning Instrument - Flood API to ensure that ATO's most vulnerable clients keep their heads above water - literally.
There is clearly some existing strategies in place for centre placement, for example data showed moderate correlation between placement of centers and the numbers of retirement villages in the area. However, there was no correlation between areas with high levels of tax related personal insolvencies and the placement of the centres. This is likely due to the ATO not have access to such data and demonstrates the utility of data sharing between government departments.
See below:
Description of Use Key income tax return data from the ATO in this dataset was used to target postal areas mostly likely to have eligible low income earners (i.e. pursuant to ATO policy under $60,000) and ABS demographic data from the this dataset was used to target vulnerable groups such as students and seniors.
Description of Use Flood zoning data was extracted from the SEED Environmental Planning Instrument - Flood API to ensure that ATO's most vulnerable clients keep their heads above water - quite literally.
Description of Use ABS demographic data from the GovhackATO dataset and geo-locations of technical schools, that is Post secondary (TAFEs) educaton excluding University, from NSW spatial APIs was combined to target vulnerable students for ATO's tax help program. This dataset was combined with ATO Tax Help Centre data in the Govhack ATO dataset via mapping longitude and latitude geo-locations in this dataset to the ABS postal areas keyed data in the Govhack ATO dataset.
Description of Use ABS demographic data from the GovhackATO dataset and geo-locations of retirement village from NSW spatial APIs was combined to target vulnerable seniorsfor ATO's tax help program. This dataset was combined with ATO Tax Help Centre data in the Govhack ATO dataset via mapping longitude and latitude geo-locations in this dataset to the ABS postal areas keyed data in the Govhack ATO dataset.
Description of Use Team Placeholder used simple natural language processing ("NLP") to identify and extract data from this dataset related to tax related insolvencies and used this to identify key under-served areas for the ATO's tax help program. This dataset was combined with ATO tax return data and ABS demographic data in the Govhack ATO dataset via mapping S3A keyed information in this dataset to the ABS postal areas keyed data in the Govhack ATO dataset.
Eligibility: This challenge will award a prize to the best pitch that combines two or more NSW spatial datasets in a proposal that delivers value to the people of NSW.
Go to Challenge | 14 teams have entered this challenge.
Go to Challenge | 15 teams have entered this challenge.
Go to Challenge | 21 teams have entered this challenge.
Eligibility: Use at least two data sets (at least one from data.gov.au) to help government make a decision that will improve services for people. Any code produced for your entry must be published on github under an open license. If your entry is not software, you will need to show the working behind your use of data along with any calculations and analysis you did. You must indicate which specific government agency (at any level of government) can take action based on your entry.
Go to Challenge | 58 teams have entered this challenge.
Go to Challenge | 61 teams have entered this challenge.
Eligibility: Use at least one dataset from SEED as central element, plus feedback on potential improvements to it.
Go to Challenge | 11 teams have entered this challenge.
Go to Challenge | 13 teams have entered this challenge.
Go to Challenge | 19 teams have entered this challenge.
