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Team Name:

Insight Hackers


Team Members:


Evidence of Work

SoloNav

Project Info

Insight Hackers thumbnail

Team Name


Insight Hackers


Team Members


7 members with unpublished profiles.

Project Description


SoloNav

Extracting information from open Government datasets can be a frustrating and overwhelming process. Data analysists and researchers spend more than 80% of their time trying to find accessible, reliable and up-to-date resources (Quora, 2018).
Issues with the current open sources data bases
Connectivity – there are issues with collaboration and connectivity - as Government datasets are set up to be highly siloed in specialised systems which use proprietary data schemas. Vendors have little incentive to collaborate or integrate as they have a vested interest in creating a monopoly. Therefore it’s difficult to connect multiple API’s across multiple systems into one simple solution.
Complexity – there are huge complexity issues regarding disparate data sources, formats, schemas and scalability, which lead to poor data quality and low levels of data maturity across the industry.

Personalisation – current solutions do not enable multiple datasets to be compared, correlated, nor customised in a way that can be easily tailored to suit the needs of the individual user or benefit the community in a meaningful and collaborative way.

Benefits of SoloNav
Accessible - SoloNav provides a one-stop shop where users can access multiple open datasets and derive searchable metadata in an efficient manner.
User Friendly - It enables users to find insights in a quick, easy and simple way, when navigating through multiple complex data sets
Story telling – users can extract and tell powerful stories through correlations of different features and datasets, using data journalism and visualisation.
Insights – users will feel more empowered to make better decisions, by identifying the latest performance trends and insights.
Community – SoloNav helps to bridge the gap between academia and industry, and helps to increase collaboration, innovation, awareness and deliver better services for the overall community.
Sustainable– SoloNav enables councils to provide short and long-term recommendations for local initiatives, to help reduce environmental impacts and stimulate local communities’ economies.


Data Story


Which data sets were used?
Here are some examples of the used data
Australian Bureau of Statistics
Description of Use: Used to download detailed statistics from 2016 Australian Census. Data was used to compare different municipalities (Kingston, Casey & Wyndham). Individual Council statistical data sets were analysed and compared to the raw ABS data and combined to provide a demographic profile of the three municipalities.
VIF 2016 LGA Kingston -
Description of Use: The one page summary was analysed to find key insights of the Kingston demographics, this was then used to download additional raw data from the ABS Table Builder.
Australian Institute Health and Welfare (aihw.gov.au)
Description of Use: This data was analysed to determine whether there is an increased cost to government for health care due to our ageing population. This was used to reinforce the Ageing population statistic as the key statistic to focus on as a performance metric.


Evidence of Work

Video

Team DataSets

City of Casey Transport Data

Data Set

Rubber recovery in Victoria (part of the Victorian Recycling Industry Annual Survey)

Data Set

Participation in Sport and Physical Recreation, Australia, 2013-14

Description of Use Used to download detailed statistics from 2016 Australian Census. Data was used to compare different municipalities (Kingston, Casey & Wyndham). Individual Council statistical data sets were analysed and compared to the raw ABS data and combined to provide a demographic profile of the three municipalities.

Data Set

VIF 2016 LGA Casey - One Page Profile

Description of Use Used to download detailed statistics from 2016 Australian Census. Data was used to compare different municipalities (Kingston, Casey & Wyndham). Individual Council statistical data sets were analysed and compared to the raw ABS data and combined to provide a demographic profile of the three municipalities.

Data Set

Australian Institute Health and Welfare (aihw.gov.au)

Description of Use This data was analysed to determine whether there is an increased cost to government for health care due to our ageing population. This was used to reinforce the Ageing population statistic as the key statistic to focus on as a performance metric.

Data Set

VIF 2016 LGA Kingston - One Page Profile

Description of Use The one page summary was analysed to find key insights of the Kingston demographics, this was then used to download additional raw data from the ABS Table Builder.

Data Set

Australian Bureau of Statistics

Description of Use Used to download detailed statistics from 2016 Australian Census. Data was used to compare different municipalities (Kingston, Casey & Wyndham). Individual Council statistical data sets were analysed and compared to the raw ABS data and combined to provide a demographic profile of the three municipalities.

Data Set

Challenge Entries

Bounty: Industry meets Academia

How can we overcome the cultural differences between business and researchers to encourage innovation and collaboration?

Go to Challenge | 12 teams have entered this challenge.

Telling Stories with Data(.Vic)

Accessing any of the datasets on data.vic, this challenge asks participants to extract and tell stories from data. Alternatively how might we facilitate citizens’ own inquiries and investigations via the Victorian Government Open Data Portal?

Go to Challenge | 21 teams have entered this challenge.

Helping the community realise we’re in their corner!

Local Government has lots of data, so how can we utilise the data we have, and the open data out there to tell the story of what we do, how we do it so well, and how this benefits the community, in ways that constituents will receive and understand?

Eligibility: Must focus on City of Kingston

Go to Challenge | 11 teams have entered this challenge.

Casey Movers and Shakers Award

How can we better target investment into road safety and network improvements in the City of Casey?

Go to Challenge | 8 teams have entered this challenge.

Bounty: Mix and Mashup

How can we combine the uncombinable?

Go to Challenge | 61 teams have entered this challenge.

Growing Wyndham

This challenge aims to develop innovative new ideas to help plan for Wyndham as a growing city. Winning entry will be a best concept/product that is useful for the people of Wyndham.

Go to Challenge | 15 teams have entered this challenge.

Australians' stories

What meaningful ways can we tell the story about what it's like to be an Australian, and in what ways some Australians live very different lives than others? How can we make people more aware of the issues facing themselves and others as they go through life?

Go to Challenge | 34 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.

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.

Bounty: Making open data more open.

How can open data be presented on search.data.gov.au to make it easier and friendlier to use? Does this mean making it more similar to using standard search engines, like Google, or something else entirely?

Go to Challenge | 34 teams have entered this challenge.