Urban Hob·art

Project Info

Team Name


Project Art


Team Members


1 member with an unpublished profile.

Project Description


The city of Hobart is fortunate enough to host an impressive collection of urban artwork, which is noticed and admired by locals and visitors alike on a daily basis. However, these diverse pieces of artwork are often difficult to locate, and are lacking additional context about the artists, and the vision behind the artworks' creation.

Our project aims to bridge the gap between Hobartian and artwork, by creating a comprehensive directory of the urban artwork that exists around Hobart. Visitors to the site will be able to locate various pieces of artwork in their current location, and see additional information about each piece of artwork, including who the artists are, what materials the artwork was created from, when the it was created, and, most importantly, where it is located. Of special interest are descriptions of the artwork provided by the artists themselves, who share intriguing insights into their ideas behind the artwork's conception, and its original purpose.

On the application related artworks are grouped together, so visitors can discover related pieces of artwork such as artwork by the same artist, part of a single collection, and created with similar materials.

One of the most important features is a fully interactive map that is constructed around the visitor's current location, and allows them to discover artwork in a close vicinity. With this, a visitor to Hobart, or someone who lives here, will be fully equipped to discover and explore the true wealth of urban artwork that Hobart has to offer, supporting and appreciating the work of our local artists.


Data Story


Our project is built upon the Urban Art datasets provided by the City of Hobart council. The datasets already provided the majority of what we required, but required a fair amount of processing to transform it into a consistent and useful format. We combined multiple datasets containing urban artwork to create a more complete picture of the artwork available around Hobart.


Evidence of Work

Video

Homepage

Team DataSets

Urban Art Walls

Description of Use This dataset is significantly smaller than the Urban Art dataset, so it has a smaller influence over the application as a whole. In order to provide consistency across the website, this data was processed to match that in the larger dataset. The data was downloaded in CSV format and then processed with a Python script to transform it into JSON format. The missing latitude and longitude data was filled in using the Google Maps Geocode API, in order to provide greater consistency with the larger dataset, and the images were downloaded. optimised and renamed for better accessibility.

Data Set

Urban Art

Description of Use This dataset is the primary engine behind our site. It contains the titles, descriptions, photos, locations, and other metadata of the artwork that together makes Project Urban Hobart. The data was downloaded in CSV format, which was then parsed with a Python script to normalise the data and convert it into JSON format, which served as the data source for the website. Images were downloaded from the provided URLs, and the Google Maps Geocode API was used to ensure addresses were valid, and provide more accurate location data.

Data Set

Challenge Entries

Best use of Local Council Data

How can we best utilise Local Council data.

Go to Challenge | 5 teams have entered this challenge.

Healthy Communities Challenge

How might we assist councils to build healthier and stronger communities?

Go to Challenge | 49 teams have entered this challenge.

Most outstanding Tasmanian Benefit

How can we use data to benefit residents of the state.

Go to Challenge | 10 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.