Brief: A city planner from Transport for London, who uses a screen reader, needs to evaluate which boroughs are underserved by step-free stations. They’ve asked us to present a borough-level summary dashboard using the new dataset, with filtering by key features like toilets, lifts, and walking distance from attractions.
Upload to Tableau Public or Power BI Service. Ensure the dashboard:
- Uses semantic ordering of text objects
- Has accessible alt text for maps and KPIs
- Avoids any content that screen readers cannot parse (e.g. tooltips only)
- Includes keyboard-shortcut info in the dashboard’s “About” section
🎯 Key Requirement:
Demonstrate how a screen reader user can move through all dashboard components and understand key takeaways.
The brief is looking at tube station at a borough level so I pulled in some data to map tube station names to their borough. This also led me to have the dashboard display data for a single borough at a time which is controlled by a filter in the About panel on the right (except for the top 3 table at the beginning).
My decision to have the About panel on the right was based on wanting the user to look at the interesting information first to capture their attention. However, I do think having it on the left where it is likely to be read first is a completely viable option as well. Within the about panel are instructions on how to navigate the dashboard using the keyboard and some filter controls for the charts.
The idea of the top 3 table is to quickly display the boroughs that have the least amount of step-free stations. I opted to not display the data as a percentage or fraction but as a sentence to make it more readable for those with dyscalculia.
The map clearly shows which stations in a borough are step-free or not and although the legend is explained in the chart caption they could be displayed as a visual key/legend. Ideally, the attractions in the selected borough would also be displayed.
The title for the last bar chart could be rephrased as it currently does not align with the use case for someone working as a city planner for the Transport for London. When multiple attractions are shown 'all' is displayed, given more time an aggregate calculated field could list out all the relevant stations associated with the attractions in the bar chart.
To improve the overall aesthetic of the dashboard, some dividers to separate sections that are not directly related could be used. Finally, finetuning the spacing within the about panel so that the relevant controls line up with the relevant charts.