Emboiable

Project Info

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Project Description


Our project aims to help young adults better understand and visualise their career oportunities by providing tools to explore how geographic regions interact with jobs.

Users have two main ways of interacting with our site. Users can choose an industry they are interested in (such as "medicine" or "science") and explore the markets for these jobs in different cities. Alternitively, users can instead choose a city they are interested in (e.g. "Canberra" or "Perth") and get information about the jobs market, including median salaries, cost of living, and predicted 5-year growth. We use these factors to rank different fields to give the users suggestions for growing or profitable industries within their city of choice.

Emboiable works by combining data drawn from the Australian Tax Office, the Department of Employment, Skills, Small and Family Business, and crowd-sourced Cost of Living (COL) data into a cohesive description of current and future labour markets, and visualises them through a Flask webapp. This data can be easily updated as times goes on, and could be feasibly expanded to include more cities than the 9 largest included in this trial.

Note that we are currently using dummy data for our demo search, but we have real data set up for linking. To make this tool live, we would simply need to link our backend into the front-end.


Data Story


Our project uses three main sources of data.

First, we use the ATO Taxation Statistics dataset (currently the 2016-2017 financial year) to get the median salary for a wide range of industries and jobs in different states. Next, we use crowd-sourced cost of living data to adjust salaries to find earnings after living costs. Finally, we use the Labour Market Information Portal's 2018 Employment Projections to provide data to the user about the future growth of potential industries over the next 5 years.


Evidence of Work

Video

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Team DataSets

Cost of Living in Australia

Description of Use: We use this data to estimate the cost of living in different cities. We provide the option to our users to either look at city centre rents or outside centre rents, which we do by drawing both costs from this dataset.

Data Set

2018 Employment Projections - Occupational Projections to May 2023

Description of Use: We use this dataset to provide predictions of how much a queried job will grow over the next 5 years. Since this data is predicted on a national level, we assume the trends will be relatively universal to allow us to use this data with our state-level predictions.

Data Set

Taxation Statistics 2016-17 - Key individuals statistics by state/territory (Table 7E)

Description of Use: Our project uses this data to provide salary estimates for different jobs depending on their states. We make the assumtion that the majority of the income for high-education jobs (e.g. scientists) is earned in major citites, allowing us to extrapolate the state-level data to their respective major cities.

Data Set

Challenges

๐ŸŒŸ Canberra 2029 โ€“ Inclusive; Progressive; Connected

How do we use data from the past to predict a better future for Canberra? How do we best support the diversity of our community? Optimise the way we travel and transport goods throughout our city? Predict the jobs of the future โ€“ and the skills needed for them? Connect our citizens with their environment?

Go to Challenge | 21 teams have entered this challenge across all checkpoints that have passed.

Australiaโ€™s Future Employment

Choose one of the following questions to address: 1. How can recent and future changes in the labour market help prepare young people for job opportunities? 2. What can we learn from case studies of regional labour markets? For example, what does rapid change in the industries or occupations within a region tell us about the needs of employers/workers in other regional labour markets

Go to Challenge | 38 teams have entered this challenge across all checkpoints that have passed.

ATO for individuals

How can ATO and other Australian public data be used to help the community fill employment opportunities?

Go to Challenge | 27 teams have entered this challenge across all checkpoints that have passed.

Canberra 2029 โ€“ First Hackers: Inclusive; Progressive; Connected

How do we use data from the past to predict a better future for Canberra? How do we best support the diversity of our community? Optimise the way we travel and transport goods throughout our city? Predict the jobs of the future โ€“ and the skills needed for them? Connect our citizens with their environment?

Go to Challenge | 10 teams have entered this challenge across all checkpoints that have passed.

๐ŸŒŸ The Class of 2025

Considering the growing and emerging economic industries, how can data be used to assist tertiary education providers in developing courses that are relevant to, and supportive of future job creation?

Go to Challenge | 10 teams have entered this challenge across all checkpoints that have passed.

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