CASE STUDY
COVID-19 Dashboard: Rethinking Ontario’s data display for better public awareness
Designed to visually present key performance indicators (KPIs) more effectively, aligning pandemic-related data with the province’s evolving public health guidelines.
Overview
DASHBOARD
CHALLENGE
According to data from CTV News in Ontario, there is a pressing issue regarding the comprehension of the new stay-at-home rules. Many residents in the province are finding it challenging to interpret and act upon the COVID-19 data provided.
GOALS
- Provide useful information for decision-making at the local level.
- Improve data readability.
- Make it easier to find decentralized content.
- Help Ontarians visually understand lockdown rules.
PURPOSE
The main focus of the analytical dashboard is to present data variances to the user to quickly convey critical input to users, providing one-stop information used for analysis and decision-making clearly.
UX Audit & Insights
As for most Ontario dashboards, the relevant data is presented in a way that is rather confusing and not intuitive to use. The data insights were more focused on the general overview of COVID-19 and its main indexes in the province (including data on hospitalization and death) rather than on the presentation of the data that may be useful to a user in order to respond to the situation in a certain area.
To understand what people are talking about regarding the pandemic, I used a brief method to unearth useful insights from a word cloud of public Twitter data about COVID-19 in Ontario. From this dive into the data, I was able to understand what’s most troubling people: public health measures, economic impact, and restrictions.
INSIGHT CLUSTERING
Based on the findings, I organized the major issues, turning them into potential opportunities to be explored and grouping the topics by similarity so that the requirements could be analyzed later in the project.
User Profiles
To characterize the exponential behavior of the pandemic was taken as a reference for this project the Susceptible-Infected-Removed (SIR), an epidemiological model based on socio-behavioral factors.
This model allowed me to categorize users into three distinct segments: Susceptible, Infected and Recovered.
- Susceptible: Individuals who are at a high risk of contracting the disease.
- Infected: Individuals who are currently infected and capable of spreading the disease.
- Recovered: Individuals who have previously had the disease, recovered, and now have temporary immunity.
User Goals, Tasks, and Actions
Having gained a full understanding of user profiles and applied the Goals, Tasks, and Actions approach, I was able to determine the user’s intent, the tasks required to achieve it, the actions the user should take to complete them, and the path they should follow. It was crucial to define these elements for the Susceptible, Infected, and Recovered user profiles to steer the dashboard design and ensure that the platform's features align with the specific requirements and goals of each profile.
This approach to using action data based on user profiles helped me determine whether the dashboard was complicated and confusing for users, or whether users had no problems navigating it. Among the available key metrics, we selected Task Completion Rate and Time Spent on Tasks because they are practical for assessing users' interaction with the dashboard and the efficiency of its features.
Information Architecture
Through a comprehensive understanding of each user profile, I was able to identify the features that shaped how our information dashboard was structured. The dwellers' frequent questions dealt with the new rules, not just receiving updated information about the pandemic. Thus, it was necessary to create a visual representation to help lay users understand the correlation between the pandemic and lockdown rules, based on the main insights.
Data representation
Based on the findings made in the first and second phases, it was possible to enable users to easily puzzle through several variables in the data sets and to understand how certain data points stand in relation to the general picture. Thus, having identified a link between users’ needs and data visualization, we effectively presented both relative and absolute values to help users make informed decisions and understand the correlation between pandemic data and lockdown rules.
Defining the containers
I designed the layout of the containers in a continuous flow to facilitate scanning on the dashboard, prioritizing the information in a natural reading pattern, and adhering to the Western left-to-right, top-to-bottom progression on the desktop version. The continuous flow can also improve the user experience by promoting retention, allowing the user to absorb and remember the information presented more effectively. As a result, I sketched a compelling visual approach to represent complex data sets.
Sketches
I first looked at various interests and then started designing, assuming that minimalist design can be easily ported over to the new information. I have chosen to develop different menus as this approach helps to distinguish the data and makes the navigation process smoother, and user can only pay attention to certain data sets. The main goal was to make the navigation between these information blocks smooth and easy, and to make the key performance indicators easy to find. I then created the sketches on the Remarkable 2 after learning the principles of data visualization for data storytelling. Also, I established the visual hierarchy to emphasize the key information in relation to the needs stated. Therefore, it was about the time to move on to the interface once the style guide and the dashboard structure were established.
Style Guide
Grounded in Gestalt principles, the style guide adopts a clean, approachable aesthetic. The interface is intentionally reduced to its essentials, with card-based navigation that supports focus on key information and helps users quickly understand relationships across content. Navigation is reinforced through adapted icons from the Streamline library, ensuring clarity and consistency across pages. A predominantly monochromatic palette, paired with carefully placed bright accents, strengthens visual contrast and improves overall readability.
User Interface
To reduce cognitive load and maximize usability, I designed an interface that uses monochromatic components to organize information, reduce decision-making time, and emphasize priority content. Also, for the layout design, I considered one of the Principles of Calm Technology: requiring minimal user attention and preventing the user from being overwhelmed by data. Given this, I have reduced the number of elements per session and only highlighted the essentials.
DESKTOP VERSION (OVERVIEW)
DESKTOP VERSION (EXPANDED MENU)
MOBILE VERSION (OVERVIEW)
The concept project was fully responsive and customized for desktop, tablet, and mobile devices, prioritizing access to the dashboard's essential elements through a visual hierarchy.
MOBILE VERSION (MENU)
Measuring outcomes
To illustrate the potential effect of the COVID-19 Dashboard, I created an Impact Map that shows the relationship between design choices and business and financial outcomes.
At the user level, the dashboard helps people make sense of local COVID-19 data more quickly and with less effort. It displays key statistics to enable informed decisions and good community safety behaviors.
From a business perspective, the design should be easy to use so users can find the information they need without contacting support. This reduces operational pressures and increases trust in the data. Furthermore, the dashboard architecture encourages frequent visits, as people return for the latest information.
On the financial side, the predicted effects include the costs of reducing unnecessary hospitalizations and the need for additional assistance. Improved public compliance leads to fewer preventable cases, which in turn lead to more effective use of public health spending. These connections are depicted to ensure that design decisions align with strategic objectives and support a user-centred approach.
Refinement and improvements
Having reviewed the needs assessment for the people of Ontario, I designed a minimalist, multi-page dashboard to manage the growing volume of COVID-19 data. The modular architecture proved essential for organizing this extensive and specific dataset in a clear format.
Next version opportunities
The current version requires technical expertise to update the database. Developing an administrative interface would enable non-technical stakeholders to upload and integrate data directly, streamlining updates and reducing operational dependencies.
An optimized version could leverage larger screens to expand charts to full-screen and support more complex visualizations in Hospitals and Health centers, allowing users to explore granular data patterns in greater depth.
Finally, conducting user interviews would provide insights into how different groups adapt to the dashboard, informing data-driven design decisions that reduce cognitive load and optimize task completion flows.
Disclaimer: The COVID-19 dashboard is an sample design initiative to improve health dashboards in Ontario, Canada.
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