Description
This course introduces the foundational principles of dashboard design and guides corrections analysts through building clear, effective, and reproducible dashboards in R using Quarto, static layouts, plotly, and Shiny integration. For learners who do not use R, lessons 1 and 2 teach how to design dashboards that follow evidence-based visual design principles, connect meaningfully with stakeholders to align on key performance indicators (KPIs), and build dashboards that make operational data actionable. For people who do use R, you'll then progress through structuring a Quarto dashboard project, designing and styling static panels, embedding interactive plotly charts, and integrating Shiny components for real-time exploration.
The course begins by grounding learners in foundational dashboard design principles, ensuring visuals are accessible, uncluttered, and purpose driven. The course also describes how to engage stakeholders early so dashboards reflect real operational needs and deliver insights in formats that decision-makers trust and use.
In corrections environments, well-designed dashboards can support daily operations, highlight facility-level trends, and help decision-makers monitor incidents, populations, and recidivism. Automating these dashboards with Quarto ensures that updates are reproducible, version controlled, and shareable with stakeholders in a consistent format.
Intended Audience
This course is designed for corrections analysts, data specialists, and operational staff who want to create dashboards. Learners who take Lessons 3–5 should have basic R experience and familiarity with Quarto or R Markdown but need not have prior dashboard or Shiny expertise. For those without R experience, the first two lessons provide a foundation for dashboard development that can be applied to any tool.
Learning Objectives
| Objective |
|---|
| Apply design principles to create dashboards that balance clarity, accessibility, and effective data storytelling. |
| Engage stakeholders to define appropriate metrics, KPIs, and data refresh schedules for corrections dashboards. |
| Build static dashboard layouts using Quarto's grid and column structures to arrange charts and tables. |
| Embed interactive Plotly charts into Quarto dashboards for dynamic exploration of corrections trends. |
| Integrate Shiny components within Quarto dashboards for fully reactive user interfaces and live data interaction. |
Course Structure
The course is organized into lessons that should be completed sequentially. Each lesson includes a video introduction, demonstrations of key techniques, and a practical exercise that allows learners to apply the concepts presented.
Lesson Objectives
| Lesson | Objectives |
|---|---|
| Lesson 1: Dashboard Design Principles |
|
| Lesson 2: Connecting with Stakeholders |
|
| Lesson 3: Building Static Dashboard Layouts with Quarto |
|
| Lesson 4: Enhancing Dashboards with Plotly Interactivity |
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| Lesson 5: Integrating Shiny in Quarto Dashboards |
|
Resources
| Resource |
|---|
| Quarto website |
| R Markdown: The Definitive Guide — Yihui Xie, J. J. Allaire, and Garrett Grolemund |
| R for Data Science (2nd Edition) — Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund |
Estimated Time to Complete
10 hours
Keywords
R, Quarto, Dashboards, Data Visualization
