Library

A curated directory of color tools, palettes, and references — 225 entries, each chosen and annotated by hand.

A hand-curated directory of color resources — 225 entries, each chosen and annotated by one curator.

Accessibility

• Viz Palette: Preview chart colors as marks and a legend, with a color-vision simulation, before you commit to them. — Susie Lu
• Contrast Ratio Calculator: One color pair, its WCAG contrast ratio, and whether it passes for body text. — Lea Verou
• Color Review: Run a palette through protan, deutan, and tritan simulations side by side. — Anton Robsarve
• Contrast Grid: Every foreground against every background in a palette, each cell marked pass or fail for WCAG contrast. — EightShapes
• Accessible Palette: Edit a palette’s lightness and hue while the WCAG contrast of every step stays in view. — Eugene Fedorenko
• Color & Contrast: A primer on how lightness difference drives contrast, with a checker for the pair you’re testing. — Nate Baldwin
• WebAIM Contrast Checker: The standard WCAG contrast check for a text pair — the one most audits cite. — WebAIM
• APCA Contrast: APCA’s perceptual lightness-contrast score, proposed as a replacement for the WCAG 2 ratio. — Andrew Somers
• Color Oracle: A free desktop app that filters your whole screen through protan, deutan, or tritan vision. — Bernhard Jenny & Nathaniel Kelso
• Color Universal Design (CUD): A guide to figures that survive color-vision deficiency, and the source of the eight-color Okabe–Ito palette. — Masataka Okabe & Kei Ito
• Understanding LMS-based Color Blindness Simulations: How CVD simulators work — Brettel, Viénot, Machado — and where open-source versions get the math wrong. — Nicolas Burrus
• Who Can Use: Enter a color pair and see which vision types can read it, and roughly how many people that is. — Corey Ginnivan
• Coblis Color Blindness Simulator: Upload an image and view it under each type of color-vision deficiency. — Colblindor
• Sim Daltonism: A floating macOS and iOS window that simulates color-vision deficiency over whatever is beneath it. — Michel Fortin
• Simulating Color Vision Deficiencies in the Blink Renderer: How to turn on CVD emulation in Chrome DevTools, and how Blink applies the Machado matrices as an SVG filter. — Mathias Bynens
• Coloring for Colorblindness: Edit swatches and see them as protan, deutan, and tritan viewers would, with Wong, IBM, and Tol sets preloaded. — David Nichols
• Colour Contrast Analyser: A free Windows and macOS app: eyedrop any two on-screen colors for a WCAG contrast verdict. — TPGi
• DaltonLens: A desktop utility for colorblind users: click a color on screen and highlight every region that shares it. — Nicolas Burrus
• DaltonLens-Python: Reference Python implementations of the Brettel, Viénot, and Machado CVD simulations, for testing and comparison. — Nicolas Burrus
• Colorblindly: A Chrome extension that simulates each type of color-vision deficiency on any live web page. — Andrew VanNess

Colormaps

• ColorBrewer 2.0: Map color schemes filtered by class count, scheme type, print safety, and colorblind safety. — Cynthia Brewer
• CARTOColors: CARTO’s sequential, diverging, and qualitative schemes for thematic maps, including Bold, Prism, and Safe. — CARTO
• Scientific Colour Maps: Perceptually uniform, colorblind-friendly maps such as batlow and vik, built to replace rainbow scales. — Fabio Crameri
• cmocean: Oceanography colormaps — thermal, haline, dense, and more — each matched to the variable it encodes. — Kristen Thyng
• Paul Tol’s Notes: Qualitative, sequential, and diverging schemes that stay distinct under color-vision deficiency, with the reasoning for each. — Paul Tol
• cpt-city: A huge archive of gradient files from GMT, GRASS, and other mapping tools, offered in many formats. — J.J. Green
• CMasher: Perceptually uniform sequential, diverging, and cyclic colormaps for Matplotlib, each previewed beside its grayscale. — Ellert van der Velden
• Vega Schemes: Names and swatches for every color scheme built into Vega and Vega-Lite. — Vega
• colormaps (Python): A Python package that gathers colormaps from NCL, CARTOColors, cmocean, ColorCET, Crameri, and more for Matplotlib. — Pratiman Patel
• MapColPal: Judge thematic-map palettes painted onto a sample map instead of a row of detached swatches.
• NASA Panoply Colorbars: The color tables that ship with NASA’s Panoply data viewer, rainbow defaults included. — NASA GISS
• NCL Color Table Gallery: NCAR’s gallery of NCL color tables, a catalog of legacy scientific maps. — NCAR
• Palettable: A Python package bundling ColorBrewer, cmocean, Tableau, and other palette collections for Matplotlib. — Matt Davis
• ColorCET: The theory and full set of Peter Kovesi’s perceptually uniform colormaps, with a test image for each. — Peter Kovesi
• Earth Engine Palettes: Palette strings for Google Earth Engine, ready to paste into a visualization call.
• Colorcet for Python: How to call Colorcet’s maps from Python, Matplotlib, and Bokeh. — HoloViz
• Bokeh Palettes: The palettes built into Bokeh, from Category10 to Viridis, with swatches for each. — Bokeh
• Choosing Colormaps in Matplotlib: Matplotlib’s guide to choosing a built-in colormap, with a lightness plot for every map. — Matplotlib
• ColorMoves: Build a scientific colormap interactively on your own data, moving color to where the values matter. — SciVisColor
• D3 Scale Chromatic: D3’s named color schemes — ColorBrewer, viridis, sinebow — as interpolators and arrays a scale can use. — Mike Bostock
• viscm: Design a colormap while watching its lightness curve and CVD simulations — the tool used to build viridis. — Nathaniel Smith & Stéfan van der Walt
• scico: Fabio Crameri’s Scientific colour maps as R palettes and ggplot2 scales. — Thomas Lin Pedersen & Fabio Crameri
• Palettize: A CLI and Python library for colormaps: terminal previews, CVD and perceptual checks, and export to GDAL and QGIS. — Alex Kovac
• Cubehelix: A colormap that spirals around the grey axis while brightness rises steadily, so it survives black-and-white printing. — Dave Green
• cmcrameri: Registers Fabio Crameri’s Scientific colour maps with Matplotlib, so batlow is one import away. — Callum Rollo
• viridis for R: viridis, magma, inferno, plasma, cividis, and friends as R palettes with ready-made ggplot2 scales. — Simon Garnier
• paletteer: Thousands of palettes from dozens of R packages, behind one consistent interface. — Emil Hvitfeldt
• ColorSchemes.jl: Julia’s colormap catalog — scientific, cmocean, Crameri, ColorBrewer, and more — with a preview of every ramp. — JuliaGraphics
• CCC-Tool: Build a continuous colormap from a specification, then test it with ΔE plots and test fields before export. — Pascal Nardini et al.
• cmap: Colormaps from Matplotlib, cmocean, ColorBrewer, Crameri, and more, with NumPy as the only dependency. — Talley Lambert
• khroma: Paul Tol’s, Okabe–Ito, and Crameri’s schemes as R palettes and ggplot2 scales, with CVD checks built in. — Nicolas Frerebeau

Palettes

• Data Color Picker: Generate evenly spaced chart palettes — multi-hue, single-hue, or diverging — from a pair of endpoint colors. — Learn UI Design
• Colormind: An AI generator trained on photos, film stills, and art that proposes five-color schemes. — Jack Qiao
• Reasonable Colors: An open color system where shades a set number of steps apart are guaranteed to pass WCAG contrast. — Matthew Howell
• Radix Colors: 12-step UI scales with separate light and dark ramps, each step assigned a job: backgrounds, borders, or text. — Radix UI
• Coolors: Lock the colors you like and shuffle the rest into five-color schemes, then export them. — Fabrizio Bianchi
• Paletton: Build complement, triad, and tetrad schemes on a color wheel, with a live preview on a sample page. — Petr Staníček
• Adobe Color: Harmony-rule schemes from a color wheel, plus theme extraction from an uploaded image. — Adobe
• Color Thief: A JavaScript routine that pulls the dominant color and a short palette from an image. — Lokesh Dhakar
• Leonardo Color: Generate UI ramps from a key color so chosen steps hit target contrast ratios against a background. — Nate Baldwin
• UI Colors: Turn one hex into a Tailwind-style 50–950 ramp, ready to paste into a config.
• Huetone: An editor for LCH design-system scales that shows contrast between steps as you drag lightness. — Alexey Ardov
• Open Color: A fixed UI color scheme with hand-tuned hue columns and matched lightness across them. — Heeyeun Jeong
• Poline: Palettes generated along curved paths between anchor colors, with the anchors and easing left editable. — David Aerne
• HD Gradients: Build multi-stop CSS gradients in OKLCH, OKLab, and other modern spaces, and compare how each interpolates. — Adam Argyle
• Colorgorical: Generate categorical palettes by weighting perceptual distance against aesthetic preference. — Connor Gramazio, David Laidlaw & Karen Schloss
• I Want Hue: Generate categorical sets that stay far apart in color space, within the hue, chroma, and lightness range you set. — Mathieu Jacomy
• Color Gradient Designer: A multi-stop gradient editor with a choice of interpolation space, for ramps that bend through several hues.
• Color Designer: A browser suite of color utilities: mixing, blending, harmony schemes, and conversions.
• Scale: Build a color ramp from a few hue, saturation, and lightness settings instead of picking each swatch. — Hayk An
• Famous CSS Palettes: A gallery of color palettes taken from well-known websites.
• Pigment by Shape Factory: A playful generator that varies color pairs under simulated lighting, for mood and illustration work. — Shape Factory
• Glasbey: A Python library for large categorical palettes that stay maximally distinct, well past ColorBrewer’s dozen. — Leland McInnes
• Supa Palette: A Figma plugin for building, storing, and syncing UI color ramps.
• Palx: Expand one base color into a full UI spectrum of hues and shades. — Brent Jackson
• Primer Prism: Tune a product color system’s hue, saturation, and lightness curves while contrast between steps stays on screen. — GitHub
• Genome Color Tool: Generate WCAG-aware design-system ramps from brand hexes and export them to Figma. — Kevin Muldoon
• Picular: Type a word and get the dominant colors of its top image-search results.
• Palettte: Smooth the steps of a palette you already have by editing its hue, saturation, and lightness curves.
• Give Me Colors: An Observable notebook for generating and tweaking lists of colors.
• ColorBox: Build UI color ramps by shaping hue, saturation, and brightness curves across the steps. — Kevyn Arnott
• Chroma.js Color Palette Helper: Build multi-hue sequential and diverging scales with Chroma.js while watching the lightness curve. — Gregor Aisch
• Nippon Colors: Traditional Japanese colors from dyes and pigments, each with its name and values.
• Phosphor: Turn a few hexes into a ramp whose lightness climbs evenly in OKLab, with CVD previews. — Joshua Stevens
• Harmonizer: Generate an OKLCH palette where every hue hits the same APCA or WCAG contrast at each step. — Evil Martians
• Atmos Palette Generator: An OKLCH palette editor with easing curves for lightness and chroma, sRGB or P3 limits, and CSS or Figma export. — Atmos
• Realtime Colors: Try a five-color scheme on a real landing-page layout, with contrast shown for each pair. — Juxtopposed
• Color Buddy: A palette editor with a linter that flags CVD, contrast, naming, and distinctness problems as you edit. — Andrew McNutt
• CSS Gradient Generator: A CSS gradient tool that switches interpolation modes and easing, and shows why RGB blends go grey in the middle. — Josh W. Comeau
• Material Theme Builder: Turn one source color into Material 3 tonal palettes and matched light and dark schemes. — Material Design
• Solarized: A sixteen-color terminal and editor scheme set by CIELAB lightness, so its accents work on light and dark backgrounds. — Ethan Schoonover
• Tailwind CSS Colors: Tailwind’s default palette, 11 steps per hue, redefined in OKLCH in v4 to reach past sRGB. — Tailwind Labs
• MetBrewer: R palettes drawn from works at the Metropolitan Museum of Art, with the colorblind-friendly sets flagged. — Blake Robert Mills
• MoMAColors: MetBrewer’s companion: R palettes drawn from artwork at the Museum of Modern Art. — Blake Robert Mills
• RampenSau: A tiny JS function that builds palettes by cycling hue while easing saturation and lightness. — David Aerne

Pickers

• HSLuv: An HSL-style picker whose lightness stays even from hue to hue. — Alexei Boronine
• OKHSV and OKHSL Color Picker: Compare HSV, HSL, Okhsv, and Okhsl pickers on the same color to see where hue and lightness distort. — Björn Ottosson
• LCh and Lab Gradient Picker: Pick two-stop gradients in LCh and Lab so the blend keeps its lightness. — David Johnstone
• HCL Wizard: Pick colors by hue, chroma, and luminance, and build HCL palettes for R. — Achim Zeileis
• OKLCH Color Picker: Pick colors in OKLCH on the same axes as the CSS function, with sRGB and P3 gamut warnings. — Evil Martians
• LCH Colour Picker: A CIE LCH picker that flags when a color leaves sRGB or P3 and maps it back in. — Lea Verou & Chris Lilley
• pastel: A command-line tool to convert, mix, and adjust colors, pick from the screen, and generate distinct sets. — David Peter
• Pika: A free, open-source macOS eyedropper that copies colors in seven formats, OKLCH included, and checks WCAG and APCA contrast. — Charlie Gleason
• PowerToys Color Picker: A system-wide Windows eyedropper: press a shortcut, click any pixel, and copy it as HEX, RGB, HSL, CIELAB, and more. — Microsoft

References

• Color.js: A JS library for the CSS Color specs: convert, interpolate, and gamut-map across OKLab, OKLCH, P3, and more. — Lea Verou & Chris Lilley
• Culori: A functional JS color library for converting, interpolating, and measuring difference across many spaces. — Dan Burzo
• Chroma.js: A JS library for color scales and interpolation, and the engine behind the Chroma.js palette helper. — Gregor Aisch
• D3 Color: D3’s color module: parse, convert, and adjust RGB, HSL, Lab, HCL, and cubehelix colors. — Mike Bostock
• Mixbox: A pigment-mixing model whose blends behave like paint, so blue and yellow make green instead of grey. — Šárka Sochorová & Ondřej Jamriška
• Artist Pigments: A database tying pigment names and chemistry to measured color, for matching paint.
• A Dictionary of Color Combinations: A digital edition of Sanzo Wada’s 1930s Dictionary of Color Combinations, browsable by pairing. — Sanzo Wada
• spectral.js: A JS library that mixes colors by spectral reflectance, so blends follow pigment curves. — Roel van Wijnen
• colorspace: An R package for HCL palettes, CVD emulation, and palette diagnostics. — Achim Zeileis
• Awesome Colour: A community link list of color-science papers, libraries, and tools. — colour-science
• ColorAide: A Python library for conversion, interpolation, gamut mapping, and difference metrics across a very large set of spaces. — Isaac Muse
• CSS Color Module Level 4: The CSS Color 4 spec that added oklch(), lab(), and color() for wide-gamut spaces. — Tab Atkins Jr., Chris Lilley & Lea Verou
• CSS Color Module Level 5: The CSS Color 5 spec: color-mix(), relative color syntax, light-dark(), and contrast-color(). — Chris Lilley, Una Kravets & Lea Verou
• MDN: oklch(): MDN’s reference for oklch(): arguments, ranges, examples, and browser support. — MDN
• Material Design 3 Color Roles: How Material 3 assigns tonal-palette colors to UI jobs like primary, surface, and outline. — Google
• Colour: A Python color-science library covering spectral data, colorimetry, and appearance models. — Thomas Mansencal
• Comprehensive Color Solutions: CAM16, CAT16, and CAM16-UCS: The paper defining CAM16 and CAM16-UCS, successor to CIECAM02 and the model under Material’s HCT. — Changjun Li, Zhiqiang Li, Zhifeng Wang, Yang Xu, Ming Ronnier Luo et al.
• The CIEDE2000 Color-Difference Formula: Implementation Notes: Implementation notes and test data for ΔE2000, including the reference pairs that catch buggy code. — Gaurav Sharma, Wencheng Wu & Edul Dalal
• Twenty-two Colors of Maximum Contrast: Twenty-two colors chosen to stay distinguishable in sequence — the ancestor of every maximally distinct palette. — Kenneth Kelly
• Frequently Asked Questions About Color: The Color and Gamma FAQs: luminance versus lightness, gamma, and the CIE terms color code often gets wrong. — Charles Poynton
• Bruce Lindbloom’s Color Math: The reference for color math: working-space matrices, chromatic adaptation, equations, and a calculator to check against. — Bruce Lindbloom
• Handprint: Color Vision: An exhaustive, footnoted treatise on color vision, color wheels, and pigment mixing, written for watercolorists. — Bruce MacEvoy
• Color Appearance Models: The textbook on appearance models beyond CIELAB — CIECAM02 and kin — and the viewing effects they predict. — Mark Fairchild
• @texel/color: A small, fast JS library for OKLab, OKLCH, Okhsl, and gamut mapping, built for generative art. — Matt DesLauriers
• Material Color Utilities: Google’s reference code for HCT, tonal palettes, dynamic color, and image quantization, in five languages. — Material Foundation
• colorspacious: A Python library for CIECAM02, CAM02-UCS, and CVD simulation — the math viridis was designed with. — Nathaniel Smith
• gdaldem color-relief: GDAL’s docs for coloring a raster from a text color table — the format QGIS, GMT, and colormap exporters write. — GDAL
• Gamut Mapping Playground: Run out-of-gamut colors through a dozen mapping methods and compare them by ΔE and hue shift. — Lea Verou et al.
• Carbon Data Visualization Color Palettes: IBM’s categorical, sequential, diverging, and alert palettes for charts, in light and dark themes. — IBM
• Urban Institute Data Visualization Style Guide: A public chart style guide with a full color system, plus templates for R, Stata, Excel, and more. — Urban Institute
• Color Names: A hand-picked list of 30,000+ color names with hex values, as JSON, CSV, and a free API. — David Aerne
• Is My Blue Your Blue?: Call a run of hues blue or green to find your boundary, then see how it compares with everyone else’s. — Patrick Mineault
• Online Color Challenge: An online take on the Farnsworth–Munsell hue test: sort tiles by hue and get a score for your color discrimination. — X-Rite
• Werner’s Nomenclature of Colours: An interactive re-creation of Patrick Syme’s 19th-century color guide, each swatch named for an animal, plant, or mineral. — Nicholas Rougeux
• World Color Survey Visualizations: Interactive views of the World Color Survey: how speakers of 110 languages named the Munsell chart. — Mikael Vejdemo-Johansson & Susanne Vejdemo

Writing

• OKLCH in CSS: Why We Moved from RGB and HSL: The case for OKLCH in CSS: lightness that holds across hues, and the syntax to replace RGB and HSL. — Andrey Sitnik
• Understanding WCAG Color Contrast: WCAG’s explanation of the 4.5:1 and 3:1 text contrast minimums, and the cases they don’t cover. — W3C
• A Perceptual Color Space for Image Processing: The post introducing OKLab: where CIELAB’s hue and lightness slip, and the transform that fixes them. — Björn Ottosson
• Color and Light: A Guide for the Realist Painter: A painter’s manual on how light, shadow, atmosphere, and pigment shape the colors you see. — James Gurney
• How to Pick More Beautiful Colors for Your Data Visualizations: Pick chart colors so lightness, not only hue, separates and orders them. — Lisa Charlotte Muth
• Subtleties of Color: A six-part NASA series on encoding earth-observation data in color, from rainbow defaults to diverging schemes. — Robert Simmon
• Datawrapper: color in data vis: Every Datawrapper blog post on color in data visualization, in one list. — Lisa Charlotte Muth
• How to Generate Color Palettes for Design Systems: Generate a design-system ramp in code from curves in a perceptual space instead of hand-picked hexes. — Matt Ström-Awn
• Color Spaces: An interactive essay on how spectra, eyes, and RGB displays combine into the colors you see. — Bartosz Ciechanowski
• Wide Gamut: A field guide to Display P3 and Rec. 2020 on the web: what changes, and where sRGB pipelines still clip.
• Coloring Maps: Linear, quantize, quantile, and Jenks scales side by side on one choropleth, and why discrete classes read better. — Adam Pearce
• How to Pick the Least Wrong Colors: A procedure for chart colors when brand, contrast, and distinctness can’t all be satisfied at once. — Matt Ström-Awn
• A Better Default Colormap for Matplotlib: The case for viridis: why jet misleads, and the perceptual constraints on a good default. — Nathaniel Smith & Stéfan van der Walt
• Color: From Hexcodes to Eyeballs: From a hex code through the display’s light and the eye’s cones to the color you report seeing. — Jamie Wong
• Color Controversy: Swatches that people name differently, and why the split in color naming is perceptual.
• Crafting Data Colors and Staying on Brand: How to keep a brand’s colors in charts without breaking the data encoding. — Observable
• High Definition CSS Color Guide: A guide to CSS color beyond sRGB: oklch(), display-p3, color-mix(), and gamut media queries. — Adam Argyle
• Thinking About Color: How Cloudflare’s design team built its product color system, and the constraints behind each choice. — Cloudflare
• Color Book Updates: Working notes and progress updates for a book on color in data visualization. — Lisa Charlotte Muth
• NASA Ames Color Usage Guidelines: Guidelines for color on displays: coding, redundancy, and when hue stops being a reliable signal. — NASA Ames
• CSS Relative Color Syntax: Derive lighter, darker, or translucent variants from an existing color with relative color syntax. — Adam Argyle
• contrast-color() in CSS: Let the browser choose a contrasting text color with contrast-color() instead of hard-coding the pair. — WebKit
• WCAG Understanding: Use of Color: WCAG’s rule that information must not depend on hue alone, separate from the contrast tests. — W3C
• Optimizing Colormaps for Color Vision Deficiency: The paper behind cividis: a viridis variant tuned so color-vision deficiency doesn’t change how the scale reads. — Jamie Nuñez, Christopher Anderton & Ryan Renslow
• Interview with Björn Ottosson: Björn Ottosson on why he built OKLab, and the tradeoffs the space accepts. — Smashing Magazine
• A Design System to Prevent Problematic Colour Pairings: How Economist Impact built its chart colors so no pair collapses under color-vision deficiency. — Ben Willers
• Chasing Rainbows: A first-person essay on color-vision deficiency and the interfaces, Wordle among them, that put meaning in hue alone. — Andy Baio
• Colors for Race, Ethnicity, and World Regions: Why common colors for race, ethnicity, and world regions aren’t neutral, and what to use instead. — Lisa Charlotte Muth
• How Software Gets Color Wrong: Why blending in gamma-encoded sRGB gives muddy results, and why HSL and HSV inherit the same flaws. — Björn Ottosson
• sRGB Gamut Clipping: How to pull an out-of-gamut color back into sRGB in OKLab without shifting its hue. — Björn Ottosson
• The Misuse of Colour in Science Communication: How rainbow and red–green maps distort scientific figures, and what to use instead. — Fabio Crameri, Grace Shephard & Philip Heron
• Advice for Colormap Selection: Practical advice on sequential, diverging, and isoluminant colormaps, with the maps ready to download. — Kenneth Moreland
• Rainbow Color Map (Still) Considered Harmful: The classic case against rainbow maps: no perceptual order, hidden structure, and invented edges. — David Borland & Russell M. Taylor II
• The End of the Rainbow? Color Schemes for Improved Data Graphics: An early plea to earth scientists to drop rainbow maps for ColorBrewer-style schemes that CVD readers can use. — Adam Light & Patrick Bartlein
• Good Colour Maps: How to Design Them: The paper behind ColorCET: a test image that exposes flat spots in a colormap, and a recipe for uniform ones. — Peter Kovesi
• Diverging Color Maps for Scientific Visualization: The paper behind the cool-warm map: interpolate diverging scales in Msh so the midpoint stays neutral. — Kenneth Moreland
• True Colors of Oceanography: The paper introducing cmocean: one colormap per ocean variable, chosen to match how each quantity behaves. — Kristen Thyng et al.
• Escaping RGBland: Selecting Colors for Statistical Graphics: The case for building statistical palettes in HCL rather than RGB, and the basis of R’s colorspace package. — Achim Zeileis, Kurt Hornik & Paul Murrell
• ColorBrewer.org: An Online Tool for Selecting Colour Schemes for Maps: Why ColorBrewer exists, and how its schemes were tested on real maps rather than swatches. — Mark Harrower & Cynthia Brewer
• Turbo, An Improved Rainbow Colormap for Visualization: A rainbow for when you need maximum hue contrast, with jet’s banding and false edges smoothed out. — Anton Mikhailov
• Color Naming Models for Color Selection, Image Editing and Palette Design: A model of the names people give colors, used to test whether a palette’s swatches are nameably distinct. — Jeffrey Heer & Maureen Stone
• Selecting Semantically-Resonant Colors for Data Visualization: Colors that match what a category means — blue for water, yellow for banana — make charts faster to read. — Sharon Lin, Julie Fortuna, Chinmay Kulkarni, Maureen Stone & Jeffrey Heer
• Modeling Color Difference for Visualization Design: How far apart two colors must be to look different depends on the mark: bars, points, and lines differ. — Danielle Albers Szafir
• Color Crafting: Automating the Construction of Designer Quality Color Ramps: Learns the curves in 222 designer-made ramps, then generates new ramps from a single seed color. — Stephen Smart, Keke Wu & Danielle Albers Szafir
• A Physiologically-based Model for Simulation of Color Vision Deficiency: The CVD model behind most simulators, Chrome DevTools included, with severity as a dial. — Gustavo Machado, Manuel Oliveira & Leandro Fernandes
• The Development and Rationale of Cross-blended Hypsometric Tints: Elevation tints that shift with climate — green lowlands in wet regions, tan ones in deserts. — Tom Patterson & Bernhard Jenny
• Palettailor: Discriminable Colorization for Categorical Data: Generate and assign categorical colors together, scored on the actual chart, so neighboring classes differ most. — Kecheng Lu et al.
• Points of View: Color Blindness: A one-page column on why red–green fails, with the Okabe–Ito set as a drop-in fix. — Bang Wong
• How We Designed the New Color Palettes in Tableau 10: How Tableau’s default categorical palette was rebuilt: balanced lightness, nameable hues, and a default’s tradeoffs. — Maureen Stone
• Bivariate Choropleth Maps: A How-to Guide: How to blend two sequential ramps into a 3×3 map legend whose diagonal still reads. — Joshua Stevens
• Designing Accessible Color Systems: How Stripe rebuilt its UI palette in a perceptual space so each step lands on a predictable contrast. — Daryl Koopersmith & Wilson Miner
• Okhsv and Okhsl: Two New Color Spaces for Color Picking: The derivation of Okhsv and Okhsl: HSV- and HSL-shaped pickers built on OKLab. — Björn Ottosson
• Programming Design Systems: Color: Free book chapters on color for programmers: a short history of color theory, color models, and procedural palettes. — Rune Madsen
• The Hitchhiker’s Guide to Digital Colour: Question-by-question answers to what an RGB value actually means, for image makers tired of guessing. — Troy Sobotka
• Using Colors on Maps: How to match sequential, diverging, and qualitative schemes to the data on a map. — Axis Maps
• The Science of Color & Design: The introduction of HCT: CAM16 hue and chroma with CIELAB tone, so contrast follows from tone numbers. — Material Design
• How We Redesigned the Linear UI (Part II): How Linear generates every theme from three inputs — base, accent, contrast — in LCH, replacing 98 hand-set variables. — Linear
• A Better Default Colormap for Matplotlib: The SciPy 2015 talk: the case against jet, and how viridis was designed in CAM02-UCS. — Nathaniel Smith & Stéfan van der Walt
• Interaction of Color: Albers’ course in seeing color relatively, in Yale’s complete digital edition with interactive plates. — Josef Albers
• A Field Guide to Digital Color: Color from perception through displays, print, and design — a bridge between color science and practice. — Maureen Stone
• Cartography.: An illustrated compendium of more than 250 map-design topics, treating color as a choice about data. — Kenneth Field
• Designing Better Maps: A Guide for GIS Users: A GIS map-design guide from ColorBrewer’s author, with a long, practical section on choosing color schemes. — Cynthia Brewer
• Easing Gradients: Replace linear gradient stops with easing curves so scrims and fades lose their hard edge. — Andreas Larsen
• Mapping Color to Meaning in Colormap Data Visualizations: Viewers read darker as more — unless a map looks semi-transparent, and then more opaque reads as more. — Karen B. Schloss, Connor C. Gramazio, A. Taylor Silverman, Madeline L. Parker & Audrey S. Wang
• Somewhere Over the Rainbow: An Empirical Assessment of Quantitative Colormaps: Nine colormaps tested on distance judgments: viridis holds up at every span; single-hue blues blur small gaps. — Yang Liu & Jeffrey Heer
• Rainbows Revisited: Modeling Effective Colormap Design for Graphical Inference: Colormaps that pass through more nameable colors, rainbows included, made people more accurate at inference. — Khairi Reda & Danielle Albers Szafir
• The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps: Turns colormap rules of thumb — order, uniformity, discriminative power — into definitions you can test. — Roxana Bujack, Terece Turton, Francesca Samsel, Colin Ware, David Rogers & James Ahrens
• How NOT to Lie with Visualization: The rainbow draws contours the data lacks; match the colormap to the task and the data’s spatial frequency. — Bernice Rogowitz & Lloyd Treinish
• Color Sequences for Univariate Maps: Theory, Experiments and Principles: Experiments separating reading values from reading shape: lightness carries form, hue helps read values. — Colin Ware
• Color Use Guidelines for Mapping and Visualization: The chapter that sorted map schemes into sequential, diverging, and qualitative — the typology ColorBrewer uses. — Cynthia Brewer
• Accessible Color Sequences for Data Visualization: Six-, eight-, and ten-color cycles tuned for aesthetics, CVD, and grayscale; the ten-color set ships in Matplotlib. — Matthew A. Petroff
• Semantic Discriminability for Visual Communication: Whether viewers can match colors to concepts without a legend depends on how distinct the colors’ associations are. — Karen B. Schloss, Zachary Leggon & Laurent Lessard
• Choosing Colors for Data Visualization: A primer: color’s first jobs are to label and group, and axes and background are part of the palette too. — Maureen Stone
• Color Survey Results: Five million color names from 222,500 sessions, with the 954 most common published as a free list. — Randall Munroe
• Computer Color is Broken: A four-minute video on why blending sRGB values without undoing gamma gives dark, muddy edges. — Henry Reich
• Better than Lab? Gamut Reduction CIE Lab & OKLab: CIE LCH bends blue toward purple as chroma drops, breaking gamut mapping; OKLab keeps the hue line straight. — Chris Lilley
• How Bad Is Your Colormap?: A short function that renders any Matplotlib colormap in grayscale, exposing jet’s bands and reversals. — Jake VanderPlas
• The Rainbow Is Dead… Long Live the Rainbow!: A series for geoscientists on what goes wrong in the rainbow, and how to build a perceptual one in CIELAB. — Matteo Niccoli
• Firefly Cartography: A recipe for glow maps: a dark, desaturated basemap, a masked highlight, and one bright thematic layer. — John Nelson
• Information Visualization: Perception for Design: The textbook on vision for visualization design, with chapters tying color theory to rules for coding data. — Colin Ware
• Choosing Color Palettes (seaborn): Seaborn’s tutorial on qualitative, sequential, and diverging palettes, with the reasoning behind its defaults. — Michael Waskom
• An Interactive Review of Oklab: Live gradients comparing Oklab with CIELAB, CAM16-UCS, and other spaces, to test how well it really works. — Raph Levien
• LCH Colors in CSS: What, Why, and How?: The case for lch() in CSS: perceptual lightness, predictable adjustments, and access to P3 colors. — Lea Verou
• Why We Use Bad Color Maps and What You Can Do About It: Why rainbow maps persist even among experts, and why making good maps the easy default beats scolding. — Kenneth Moreland
• colorspace: A Toolbox for Manipulating and Assessing Colors and Palettes: The paper on R’s colorspace: HCL palettes, CVD emulation, and plots for judging a palette before you use it. — Achim Zeileis, Jason C. Fisher, Kurt Hornik, Ross Ihaka, Claire D. McWhite, Paul Murrell, Reto Stauffer & Claus O. Wilke
• What to Consider When Choosing Colors for Data Visualization: Fifteen practical rules for chart color: when to use it, how many colors to use, and how to build gradients. — Lisa Charlotte Muth