Team Name:
Team School Data
Team Members:
Team School Data
We are providing a social software platform that can help young people and job seekers demonstrate how the soft skills and life experiences they have are valuable to employers and finding work.
Refer to data story pdf in github.
Description of Use This dataset was acquired from the ACT Government Open Data Portal and provide statistics and survey results from the local community against 12 domains which have been defined by the ACT Government to determine well being in the local community. This dataset is vital as it highlights the indicators which are scoring poorly leading to a lower sense of community well being. As a result, our platform promotes soft skill development through activities such as volunteering and community participation which enables individuals to cultivate a closer social connection, a sense of identity and a belonging to the local community.
Description of Use This dataset was acquired from the Australian Bureau of Statistics (ABS) and displays the statistics on the production of agricultural commodities on Australian Farms during the 2020-21 financial year. This database is vital as it highlights the largest agricultural industries within each state in Australia. This information can be supplemented with regional development reports and ABS census data to identify growth sectors within the Barossa, Gawler, light and Adelaide Plains region and in turn the likely skills and training which
Description of Use This dataset was acquired from the Australian Taxation Office and displays the benchmark for various industries based on reporting from the 2018-19 income year. This database is vital as it highlights key financial and activity statement ratios which provide insights into the industries where employees are investing more heavily on the development of their employees. This information would also indicate which industries are likely growing and will be heavily in demand in the future so that our platform is able to facilitate learning and development which will equip people with the right skills to be employable in these industries.
Description of Use This dataset was acquired from the Australian Bureau of Statistics and displays the results of the 2021 Australian census which provides demographic, social and economic information about people in Australia based on locality at the time of the census. This database will be vital as it highlights key information such as the proportion of individuals attending an educational institution, unemployment rates and the proportion of people who come from a family where English is not the first language. This information can be utilised to identify the regions where there is a higher proportion of disadvantaged communities who will benefit from the implementation of our platform.
Description of Use This dataset was acquired from the Victorian Department of Education and Training and displays the results of the On Track Survey 2021 which monitors the transition of school leavers six months after finishing school. Based on the results of this dataset, we were able to identify the schools and communities which displayed the highest proportion of unemployment for individuals after leaving school. As such, this data will be utilised to identify the institutions and regions where our platform can be piloted and provide a framework to assist young adults in the transition process by identifying skills gaps between an individual and their desired occupation.
Eligibility: Participants must use one or more datasets from Data.Vic to be eligible.
Go to Challenge | 12 teams have entered this challenge.
Eligibility: Use at least one ATO data set.
Go to Challenge | 6 teams have entered this challenge.
Eligibility: The project to focus on Barossa-Gawler-Light-Adelaide Plains Region.
Go to Challenge | 4 teams have entered this challenge.
Eligibility: Must use at least one ACT Government data set, either from the Open Data Portal (data.act.gov.au) or the Geospatial Catalogue (actmapi-actgov.opendata.arcgis.com).
Go to Challenge | 9 teams have entered this challenge.
