Exploring data visualization through perception, information design, storytelling and modern visualization technologies.
VisComm is an collection of teaching materials, notes, examples and experiments exploring data visualization from multiple perspectives.
Rather than focusing on charts, software or visualization libraries alone, VisComm explores the complete design process behind effective visual communication with data. It connects perception, information design, storytelling and modern visualization technologies into a coherent approach applicable across different domains—from business intelligence and dashboards to scientific visualization, education and data journalism.
An authorial approach currently being developed within the VisComm project.
Audience- and Purpose-Driven Visualization (APDV) is an authorial approach to designing data visualizations that places the audience and the purpose of communication at the beginning of the design process.
Instead of starting with the data, chart type or visualization technology, the process begins by answering three fundamental questions:
- Who is the audience?
- Why is the visualization being created?
- What understanding should it support?
The answers to these questions guide every subsequent design decision—from data selection and transformation, through visual encoding and information design, to storytelling techniques and implementation technologies.
Within this approach, charts are considered to be the result of the design process rather than its starting point.
Although visualization domains differ — business analytics, scientific visualization, dashboards, education or storytelling— the underlying design process remains fundamentally the same. What changes is the audience, the purpose and the context.
Audience → Purpose → Question → Data → Perception → Visual Encoding → Visualization → Understanding
VisComm covers, among others:
- Data Visualization
- Information Design
- Visual Communication
- Human Perception
- Preattentive Processing
- Gestalt Principles
- Visual Encoding
- Color Theory
- Typography
- Exploratory Visualization
- Explanatory Visualization
- Scientific Visualization
- Dashboard Design
- Data Storytelling
- Interactive Visualization
- ggplot2
- Plotly
- Streamlit
- D3.js
- Three.js
- Observable
- R and Python visualization ecosystems
- explore data visualization from multiple perspectives
- understand how people perceive visual information
- design visualizations around audience and purpose
- connect theory with practical implementation
- compare visualization methods and technologies
- provide reusable materials, examples and design notes
VisComm is a continuously evolving project. New notes, examples, case studies, technologies and teaching materials are added as the project grows. The Audience- and Purpose-Driven Data Visualization approach is being refined through teaching, experimentation and practical application.
Introduction to the principles of effective chart design, avoiding chart junk, and storytelling with data.
- Four Steps to Better Data Visualizations – Practical framework and key steps for creating more impactful data visualizations.
- Simplify charts (Medium) – An insightful read on why simplicity remains the ultimate goal and best friend of data visualization.
- Storytelling & Design Chart (Medium) – Straightforward design techniques and tricks to effectively capture and retain user attention.
- Edward Tufte: Chartjunk – A classic introduction to identifying and eliminating clutter from charts; excellent preparation before diving into layered graphics.
- Add Two Digital Blog – A collection of articles, insights, and inspirations focused strictly on data storytelling.
- Autodesk: Datasaurus Dozen – A brilliant demonstration of why visualizing data is critical (shows multiple datasets with identical summary statistics but completely different visual distributions).
Theoretical materials explaining the underlying architecture and philosophy of modern data visualization systems.
- Hadley Wickham: A Layered Grammar of Graphics (PDF) – The fundamental academic paper detailing the layered framework that powers modern R visualization.
- Computing for Social Sciences: Why Visualize Data? – Introduction to visualization theory, along with notes covering Grammar of Graphics, tidy data, text analysis, ML, and Shiny.
- Computing for Social Sciences: Grammar of Graphics – An accessible breakdown of the core components that make up the grammar of graphics.
- Towards Data Science: A Comprehensive Guide to the Grammar of Graphics – An in-depth, structured guide to representing multi-dimensional data visually.
- Grammar of Graphics Basics (QCBS) – Hands-on workshop materials designed to prepare learners for working with
ggplot2.
Implementation materials ranging from initial setup and comparisons to advanced, production-ready code galleries.
- Hadley Wickham: ggplot2. Elegant Graphics for Data Analysis (3rd Ed, online) – The complete, free online edition of the official handbook written by the creator of the package.
- Claus O. Wilke: Fundamentals of Data Visualization – An exceptional, highly recommended online textbook focusing on the principles of accurate and honest data presentation.
- Variance Explained: Why I use ggplot2 – A direct comparison between R's base graphics and
ggplot2(highly recommended reading!). - Variance Explained: Teaching ggplot2 to beginners – A pedagogical perspective on how to introduce this package to novices effectively.
- STHDA: Be Awesome in ggplot2 (Practical Guide) – Excellent practical guide for building highly polished, professional charts in R.
- Datanovia: GGplot Examples Best Reference – Superb reference source that covers standard plots alongside highly useful extensions and add-ons.
- Top 50 Ggplot2 Visualizations Master List – A comprehensive repository of the 50 most common chart types, complete with reproducible R source code.
- ggplot2 Quick Reference & Cheatsheet – A quick-access cheat sheet detailing fundamental functions, aesthetics, and parameters.
- The R Graph Gallery: ggplot2 section – An interactive showcase of inspiration, design ideas, and ready-to-use code templates.
- Cookbook for R: Graphs – A practical, recipe-based collection addressing common issues encountered when plotting data.
- Cookbook for R: Correlation matrix – A targeted tutorial focusing specifically on creating and styling correlation matrices.
- R4Stats: Graphics with ggplot2 – Clear examples contrasting different plotting paradigms with side-by-side code snippets.
- Ben Shneiderman’s Visualization Mantra in ggplot2 – A practical implementation of the famous UI design mantra ("Overview first, zoom and filter, then details-on-demand") using ggplot2.
For comparative analysis – tools designed for generating trellis (conditional) multipanel displays for multivariate datasets.
- Lattice Graphs (STHDA) – A straightforward, clear introduction to generating plots within the
latticeframework. - Tutorial on Lattice Package in R – A step-by-step user guide showcasing the primary capabilities of the library.
- TechVidvan: Lattice Package in R – A conceptual tutorial analyzing the internal structure and use cases of trellis graphics.
- DataFlair: R Lattice Package Introduction – Foundational theory and practical code examples for rendering multi-panel layouts.
Supplementary materials extending into general R programming mastery and academic document preparation.
- YaRrrr! The Pirate's Guide to R – An incredibly engaging, humorous, and comprehensive free textbook for learning R from absolute scratch.
- Joey Stanley: R Workshops – A valuable repository of scripts, slides, and files from advanced data analysis workshops.
- Joey Stanley: LaTeX Workshops – Practical resources and introductory guides for typesetting scientific documents and technical layouts using LaTeX.