City of toronto 24 hour hackathon winner
Project Overview: The City of Toronto boasts an exceptional open-source information delivery tool, empowering individuals with accessible datasets to explore and achieve their objectives seamlessly. The platform needed an overhaul. Datasets were difficult for the public and city officials to interpret. Our team of three software developers, two UX designers, and two data scientists were tasked with presenting datasets in a valuable way to city bureaucracy and the public.
Constraints: 24 hours to delivery, JSON format datasets, City Of Toronto Brand Guidelines
Deliverables: Open Data Webpage, Functional Dashboard, Data Prediction Model, Live Map, and Pitch Presentation
Outcome: Our solution won! We delivered a fresh design of the Daily Shelter & Overnight Occupancy & Capacity dataset dashboard. This solution drove users to be able to easily interpret the most valuable data helping them make informed decisions. Users include academic researchers, city officials, and social workers.
and so it begins..
We began by immersing ourselves in the Open Data platform, diving into its extensive collection of datasets. The challenge arose when we realized that the information, crucial for both the general public and city officials, was inherently complex and challenging for individuals without a technical background to interpret.
This prompted us to explore ways to enhance accessibility and make this invaluable resource more user-friendly.
After carefully evaluating five datasets, we opted for the 'Daily Shelter & Overnight Occupancy & Capacity' dataset. Recognizing its immense significance amid the housing crisis, we believed it held substantial value for both the general public and city administration. This informed our decision to refine the 'How Might We' question initially presented by the City of Toronto.
How Might We..
present Open Data in a valuable way to both city bureaucracy and the general public?
present the ‘Daily Shelter & Overnight Occupancy & Capacity’ dataset in order to inform the city and general public about how to better support people in need?
How Might We..
To comprehend the significance of this dataset, we conducted thorough secondary research and obtained crucial homelessness metrics from our team of data scientists:
9000+
people without housing every night¹
98%
occupancy rate of Toronto shelters every night¹
61
shelters in the city²
To harness the potential of the dataset in aiding the vulnerable population, we crafted a compelling persona and streamlined task flow tailored for individuals we identified as beneficiaries of the Open Data platform.
We designed a straightforward task flow illustrating Natasha’s journey to access Open Data, more specifically the dataset relevant to shelter occupancy. However, at the crucial fourth step, she encounters a roadblock. The complexity of the Open Data interface proves to be a significant challenge, particularly for someone without a data background like hers. This impediment hinders her ability to effectively assist her clients, highlighting the urgent need for a more user-friendly solution.
After defining the task, we initiated the sketching phase, producing multiple design solutions for implementation. Our commitment to keeping Open Data as a webpage played a crucial role in directing the layout of the sketches. We prioritized placing the most valuable data from the set at the forefront, ensuring it is immediately accessible upon landing on the page.
Time to bring those sketches to life with digital wireframes! Working with Toronto Open Data, we danced within the brand's visual parameters. No one likes a sudden change, right? So, we kept the same colours, typography, and layout as the current Open Data site—seamless and familiar for our visitors.
Before
After
In our revamped dashboard, critical statistics take the spotlight, complemented by a dynamic live map featuring real-time data. Users can effortlessly search for a shelter, receiving pertinent information like occupancy rates. Thanks to our data model predictions, users can even glimpse into the future occupancy rates. The search bar also allows users to input an address, instantly populating the map with nearby shelters, each offering detailed data upon selection.
Outcome
While we of course didn't unravel the complex issue of homelessness in Toronto, we successfully tackled the question we posed 24 hours ago.
Here's our transformative approach:
Elevated data quality metrics: Placed prominently in the left sidebar, we prioritized showcasing the accuracy and comprehensiveness of the dataset. This empowers Natasha to quickly assess the reliability of the information, ultimately saving time for her clients.
Streamlined About section: Understanding that individuals like Natasha prefer a concise experience, we condensed the About section into a dropdown menu. While readily available for those seeking more information, it remains unobtrusive for users who prefer a streamlined interface.
Visualized key data: The game-changer. We transformed the user experience by presenting critical information through numbers, graphs, and an interactive map. Big numbers highlight key dataset facts, graphs provide visual insights for easier comprehension, and the map allows users like Natasha to explore shelter locations. This not only aids individuals but also offers city officials valuable insights for informed decision-making in funding and supporting shelters."
What’s Next?
Live Data Updates: To revolutionize the user experience, envision a real-time dashboard that automatically updates key statistics. This ensures users are continually informed about any changes, fostering a dynamic and responsive platform.
Interactive Map Markers: Imagine a colour-coded map, offering an at-a-glance view of shelter statuses. By using vibrant markers, users can easily discern which shelters are full, busy, or not busy. This feature adds a layer of immediacy and clarity to the overall experience, facilitating quicker decision-making.
Personalized Graphs: Take personalization to the next level by tailoring graphs for each dataset on Open Data. This means users can engage with visual representations that align with their specific interests. Whether it's occupancy rates, trends, or other vital metrics, this personalized approach ensures the information presented is directly relevant to the user, enhancing engagement and understanding.