Fisheries and Oceans Canada · Data systems & product design
Government of Canada projectGap Analysis Dashboard
A dashboard redesign helping marine researchers find, interpret, and discuss ecosystem data.
Context
Project brief
Fisheries and Oceans Canada (DFO) is a Government of Canada department that monitors marine ecosystem variables through an internal dashboard used by scientists, analysts, and research teams. The project focused on improving data accessibility, visualization, and collaboration across a complex system of datasets. Working from the existing Ecosystem Variables dashboard, we mapped the path from first login to finding a relevant variable, interpreting its coverage, and sharing an insight with a teammate.
The problem
The existing Ecosystem Variables dashboard made it difficult for users to find relevant data, interpret coverage gaps, and collaborate effectively.
- Limited filtering and search capabilities
- Low spatial resolution in visualizations
- Lack of actionable data insights
- No integrated collaboration tools
- Poor onboarding for new users
Research & Discovery
Research goals
Research focused on how people search for, interpret, and discuss ecological data. Semi-structured interviews and usability testing with data-analysis users revealed mismatches between user expectations and system behavior.
- Understand how users search for and interpret ecological data
- Identify pain points in filtering, visualization, and navigation
- Explore how users collaborate and share insights
- Evaluate trust in data sources and timestamps
Key challenges identified
Usability testing on the original dashboard surfaced four recurring issues that shaped everything downstream.
01
Getting started
Users struggled to locate key features and were often unsure where to start.
02
Reading the heatmap
The heatmap was helpful, but users needed clearer visuals and better access to detailed data.
03
Confusing labels
Labels and sections, like account features, caused confusion and required better organization.
04
Trusting the data
Users wanted clearer information about data sources, reliability, and timestamps.
Wireframes
Low-fidelity designs
Early wireframes explored layout, structure, and core functionality before visual detail. A persistent top navigation, a search and results panel, an interactive map, a data detail view, collaboration tools, and an onboarding flow established the product architecture.
Prototype
Advanced filtering & visualization
The redesigned dashboard lets users filter by multiple variables and biogeographic regions, define custom areas directly on the map, and explore heatmaps with finer spatial detail.
- Advanced filtering by variables and regions
- Improved heatmap visualization and zoom
- Metadata transparency panel with source, timestamp, and description
- Comments and shareable dataset links
- Onboarding and guided tutorials
Design System
Reusable data components
Every screen in the dashboard is assembled from one small library, built around the departmental indigo, a light lavender panel tone, and white data surfaces. Clear hierarchy separates summary, description, technical detail, and primary action so that dense scientific content stays legible.
Dataset search
Persistent search field for locating an ecosystem variable by name or code.
Button hierarchy
Primary, secondary, and tertiary actions with one clear emphasis per view.
Checkbox states
Unchecked, checked, mixed, and disabled states for the variable tree.
Filter tree
Collapsible theme groups that let users narrow to specific variables.
Active filter tags
Removable chips that keep the current query visible at all times.
Map coverage legend
Graduated scale explaining record density across the heatmap.
Regional distribution chart
Bar chart comparing record counts across biogeographic regions.
Data detail card
Metadata panel exposing coverage, source, and publication dates for trust.
Key Takeaways
Designing for complex data systems
This project reinforced the importance of simplifying complex datasets through clear visualization and structured interaction design. Advanced functionality only creates value when expert and less-technical users can understand what the system is showing and what to do next.
As this was a Government of Canada project, a portion of the research, iteration, and stakeholder work sits behind confidentiality agreements with Fisheries and Oceans Canada and isn’t shown here.
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