Back to Projects

Team Name:

Dr Robotnik


Team Members:


Evidence of Work

Job Atlas

Project Info

Team Name


Dr Robotnik


Team Members


Geoff Pidcock , Frankie and 1 other member with an unpublished profile.

Project Description


intro

about

Work:

  • Interactive data app | github | app website
  • Exploration of ABS API data | Google Colab
  • More design documentation, full specifications and breakdown and more information on our website Website

LeanCanvas


#employment #reskill #education #classification #skills #jobs #job skills #occupations #occupation #skillset #jobseekers #jobtransition #jobpivot

Data Story


Proof1

We used the National Skills Commission Skills Classifications dataset which has a text description component for each of the titles and the ANZCO Codes.

We used the Natural Language ToolKit (NLTK) and Term Frequency–Inverse Document Frequency (TF-IDF) to take in the ANZCO titles and descriptions, break it down into keywords and create the model.

When the user inputs their text descriptions, we can repeat the process to match that to the closest ANZCO description of a role or title. By doing so we can classify them against the existing codes and find where they sit on the model, which we can display in a graphical format.

proof1
Dataset showing title and description against codes

Proof 2

This program uses another component of the National Skills Commission Skills Classifications dataset, which classifies roles against 10 core competencies and scores them on relative proficiency level. This allows us to use this as features to map out the roles and display the relative re-training required along the x-axis of the map.

The y-axis is a logarithmic output of the Labour Market Information Portal Job Vacancies Data and uses the ANZSCO_Code as a key to match with the x-axis data. This allows us to plot the job map to the user, and the graph below shows the difference between core competencies of the two roles.

The Labour Market Information Portal - IVI Job Vacancies Data set counts online job advertisements on Seek, CareerOne and Australian Jobsearch and catalogues them against state/territories.

proof2
X-axis dataset showing proficiency ratings against codes

proof22
IVI dataset showing ANZCO Codes against job vacancies for y-axis

Proof 3

We wanted to incorporate the ABS API portal to be able to show insights regarding the roles the user would look into. In this case we worked with the IT Specialist role pulling in the data, and then linking it up with the keys provided by the mentors in the slack channel.

We used this to display a heatmap of of IT Specialists by industry and size of company.

raw
ABS API Raw Data pull

keys
ABS API Data Keys provided from Mentors on Slack

heatmap
Heatmap displaying insights obtained from dataset.

Source code for ABS API Exploration at Collab

Full write-up and more at Website


Evidence of Work

Video

Homepage

Team DataSets

(ABS_IT_SUPPORT) Characteristics of IT in Australian Businesses

Description of Use Helps job seekers target the right industry and company size

Data Set

Australian Skills Classification

Description of Use Used Occupation Descriptions, Core_competencies, To assess related jobs and retraining effort.

Data Set

Labour Market Information Portal Dataset

Description of Use Used to assess job openings for a potential job type

Data Set

Challenge Entries

Exploring the National Skills Commission’s Australian Skills Classification

How can the general public learn about and be encouraged to interact with the Australian Skills Classification to identify skills within occupations, identify their own skillsets and identify transferability to other occupations of interest?

Eligibility: Participants must use the Australian Skills Classification dataset.

Go to Challenge | 25 teams have entered this challenge.

Create a solution to a customer need using the ABS Data API

We are excited to provide innovators with machine to machine access to ABS Data and see what exciting customer solutions can be created. Here is a chance to draw in ABS Data and answer an important question through visualisation, mapping or even blending with other data sources. Create a solution to a customer need using data drawn from the ABS Data API.

Eligibility: Teams are encouraged to use datasets from a variety of sources, but at least one must be drawn from the ABS Data API.

Go to Challenge | 20 teams have entered this challenge.

Youth education and employment

How might we use publicly available data to identify education and employment opportunities for our youth?

Go to Challenge | 25 teams have entered this challenge.