Click   here   or on the image above to use a working version of the dashboard.

Click here or on the image above to use a working version of the dashboard.

 

Client: Capstone project for Tamara Munzner’s graduate viz course,

in collaboration with Fisheries and Oceans Canada

My role: Data visualization, UI design, user research, data wrangling

Tools: Tableau, OpenRefine, Python, Mapbox

Full report: Available here

Problem

Salmon scientists for Fisheries and Oceans Canada need to be able to access, explore and rapidly understand large salmon data sets, but lack the tools to do so easily and efficiently. I developed a dashboard that would allow users to quickly explore data from Fraser River salmon.

Process

Background

Fisheries scientists help to determine when and where to conduct fisheries, based on routine analysis of available data. However, this analysis can be impeded by a lack of user-friendly tools. Following a VIVA project using salmon data, I was invited to join a team called “The State of the Salmon” (SoS). My role was to help them consolidate available data from Fraser salmon populations and create a simple, interactive interface through which managers and researchers can explore the data, identify patterns, and discover how these patterns change over time. This would be a capstone project for a data visualization course lead by Tamara Munzner

User research

To begin, I consulted experts from the SoS to identify user groups within the department and characterize their data needs. We conducted brief structured interviews with representatives from these groups to understand their responsibilities and develop a taxonomy of data-related tasks. As a result of these interview, we decided our target audience was senior science managers. These individuals are mostly concerned with high-level tasks and are broad rather than deep consumers of information, tasks that would be aided by an interactive dashboard. Specifically, senior science managers are interested in the following types of tasks:

1. Exploring the available dataset. 

2. Discovering trends and features in measures of population size and health over time.

3. Compare trends and features across different Conservation Units (CUs).

4. Discover similarities between CUs.

Visualization design

I developed a Tableau dashboard featuring geospatial and temporal representations of salmon population data. The top half of the dashboard depicts CU status and their location in both geographic (map) and quasi-geographic (tree plot) representations. The bottom half of the dashboard is a series of bar and line plots that depict measures of population size and health. The subcomponents of the dashboard are described in depth in the paper I prepared for the course.

Use scenario

A potential use scenario would be that of a science manager facing questions from non-scientists, from either within or outside of the department. Science managers are often the point of contact for media inquiries and governmental officials who are seeking general information about salmon stocks. A common query is for comment on the most recent year of salmon returns, or to describe the health of a population aggregate (such as all populations within the Fraser, all populations located in the greater Vancouver area, etc).

If a science manager received a call from a member of the press who had a general inquiry about the current state of Fraser river salmon, they could pull up the dashboard and refer first to the map and tree plot, which display status for individual populations across the entire river. The manager might browse these plots and answer that the health of populations varied throughout the watershed, as indicated by the distribution of different status glyphs across these plots, but CUs in the upper watershed tended to have lower status than those in the lower watershed. If the reporter asked if there were areas of concern, the manager could identify the CUs assigned a “red” status on the tree plot, and report those CUs to the reporter. 

If the reporter asked for follow up on these regions or for specific details about these populations, the manager could then select “Red” under the “Select Conservation Status” filter, and see plots of population measures. The manager could then browse the bar and line plots to identify trends, outliers or features across these populations. Examining these plots suggests that population size is highly variable across these CUs, but all CUs showed a reduction in total recruits beginning in the late 1990s, and these have not recovered. 

In this scenario, the visualization enables rapid exploration of the existing dataset and comparisons across CUs in a way that was not possible using the department’s existing visualizations. While there are ways to improve the visualization, this represents a significant improvement over current techniques. 

Results

This dashboard served as a proof of concept that an interactive visual interface could improve the ability of fisheries scientists to explore and consume their data. It was presented as a case study to different stakeholder groups within the DFO to secure funding for further visualization development. Based on this project, I was invited to intern with the DFO via the Mitacs Accelerate program, focusing on data visualization and user research.