About Visual Complexity
We study how complex ideas become legible. Visual Complexity is a design-first project: clear structure, disciplined encodings, and honest labels for diagrams that explain networks, hierarchies, flows, and time.
Purpose
A unified space
Visual Complexity curates, explains, and critiques diagrams that reveal structure. The aim is practical: help readers choose the right form for the job and avoid decorative traps.
Cross-disciplinary
We borrow from information design, HCI, statistics, cartography, and systems thinking. Good ideas travel; we translate them into reusable patterns.
Books & methods
Alongside examples, we summarize core literature and distill method notes: when to use a matrix vs. node-link, treemap vs. sunburst, flow vs. small multiples.
Access over novelty
Innovation is welcome, but readability wins. We favor encodings people can parse quickly over visual effects that age fast.
What We Publish
Eligible work
Diagrams that make a mechanism visible: networks, trees, flows, timelines, maps, matrices, and hybrids. Each item must state the question it answers and the encodings used.
Not strictly “complex”
Some items aren’t mathematically complex. We include them if they advance technique, teach a reusable pattern, or offer a unique conceptual frame.
Method notes
Every piece ships with short notes: data scope, layout choice, known limitations, and how uncertainty is communicated.
Respect & rights
Authors keep their rights. We reproduce small, necessary excerpts for critique and education, with explicit credit in the caption.
Editorial Method
- Question-first: define what the reader must compare, track, or explain.
- Pick the structure: hierarchy, network, flow, grid, or hybrid—chosen for mechanism, not style.
- Choose encodings: prefer position/length; use color sparingly and never as the only cue.
- Label early: plan legends and annotations before layout to reduce cognitive load.
- Prototype alternatives: matrix vs node-link; treemap vs sunburst; small multiples vs single mega-chart.
- Test at two sizes: phone and desktop; check WCAG-AA contrast and font scales.
- Document limits: sampling, smoothing, missing data, and what the view cannot claim.
Primer: Complex Networks
Why networks
When interactions matter more than attributes, model the world as nodes and links. Structure explains diffusion, robustness, and coordination.
Common patterns
Small-world shortcuts, heavy-tailed degree distributions, communities, and multiplex ties. Layout is not analysis—measure before you decorate.
Right views
Node-link for sparse maps; adjacency matrices for dense graphs; radial for hub-and-spoke stories; edge bundling for routes; small multiples for time.
Honest limits
Avoid hairballs, misleading color scales, and off-by-area comparisons. Report uncertainty and sampling bias; show what’s missing.
Origins
Visual Complexity grew out of long-form design work and recurring requests from teams who needed a single place to compare diagram types. The project consolidates scattered notes, course materials, and reviews into a compact system you can use at work tomorrow.
We continue to refine patterns, audit accessibility, and update guidance as tools and standards evolve. The baseline stays the same: structure first, readable encodings, honest labels.
Credits & Contact
Editorial & design
Visual Complexity is curated and designed by a small team focused on information design and product UX. For permissions or collaboration, use the site’s contact form.
Use of materials
We credit all authors and reproduce only what is necessary for critique and education. If something needs correction or removal, contact us and we will respond promptly.
Accessibility
We target WCAG-AA contrast and test layouts at multiple sizes. If you encounter barriers, tell us what failed and on which device—we will fix it.