Welcome, fellow data vis enthusiast!

• Nathan Yau - One data set, visualized 25 ways
• Santiago Ortiz - 45 ways to communicate two quantities
• DataVizProject - 1 dataset, 100 visualizations

• Andy Kirk has created a list of all the small choices that can contribute to a great visual communication piece. Good to browse through to appreciate the small (and often simple!) choices behind good design - https://visualisingdata.com/2016/03/little-visualisation-design/

• Moritz Stefaner - https://truth-and-beauty.net
• Nadieh Bremer - https://www.visualcinnamon.com
• Sonja Kuijpers - https://www.studioterp.nl 
• Gabrielle Mérite - https://www.gabriellemerite.com

• Enrico Bertini - https://enrico.bertini.io/
• Lace Padilla - https://www.lacepadilla.com/
• Jessica Hullman - http://users.eecs.northwestern.edu/~jhullman/
• Jack van Wijk @ TUe - https://www.tue.nl/en/research/researchers/jack-van-wijk

Read about it:

• A great blog and good starting point on what to consider when making color choices is written by Lisa Charlotte Rost - https://blog.datawrapper.de/which-color-scale-to-use-in-data-vis/
• A good article on color choices when creating palettes specifically for data visualisations, and also an introduction to the Viz Palette tool -  https://medium.com/@Elijah_Meeks/viz-palette-for-data-visualization-color-8e678d996077

Create palettes yourself:

• Viz palette - A great tool to create and edit color palettes that you then immediately see used in various types of charts - https://projects.susielu.com/viz-palette
• Color picker - A nice tool to create three different types of color palettes: visually equidistant palettes, divergent palettes, and single hue palettes - https://www.learnui.design/tools/data-color-picker.html
• Cooler.co - A very good and accessible tool to explore and create color palettes. You can also derive color palettes from images with this tool, and check for grayscale readability, colorblindness, etc. https://coolors.co

Colorblindness and color contrast checkers:

• Colororacle - Program to be downloaded. Turns your computer screen into a colorscheme as seen by someone with colorblindness (also grayscales) - https://colororacle.org/
• Online color contrast checker - https://colourcontrast.cc/
• Another color contrast checker - https://contrast.tools/

A bit more technical options:

• Chroma.js Color Palette Helper - Creating a color palette that is lightness corrected overall - https://gka.github.io/palettes/
• Colorpicker tool - This tool is a great way to get to know colorspace and play with different options (I recommend playing around with all the buttons and sliders on this page, and see what happens) The beauty of this tool is that the resulting color palettes are lightness corrected (meaning that when converted to grayscale, you still have a 'correct' ordering based on the lightness) - http://tristen.ca/hcl-picker/
• IwantHue - Creating a good looking color palettes mostly for categorical, distinct data sets - http://medialab.github.io/iwanthue/

• Karen Cheng et al. - Proving the value of visual design in scientific communication - Information Design Journal 23(1), 2017
• Tracey Weissgerber - Reveal, don't conceal - Circulation. 2019;140:1506–1518
• Fabio Crameri et al. - The misuse of colour in science communication - Nature Communications (2020) 11:5444
• Bang Wong - Points of View part 2: Color and quantitative data - Nature Methods March 2011

• Outlier - Relatively new online conference, organised by the Data Visualization Society - https://outlierconf.com
• OpenVis - Unfortunately this one has stopped after a few editions. Very much worth to check out presentations on their website or YouTube.
• Infographic Congres - Live conference in The Netherlands, a bit more focussed on journalism/infographics - https://www.infographicscongres.eu
• SciVizNYC - Focussed on scientific visualisations - https://www.sciviz.nyc
• Steve Franconeri @ OpenVis 2018 - Very interesting presentation on visual cognition: how does our brain process visual information, what is it good/bad at?
• Shan Carter at OpenVis conference, where (at 6 minutes in, lasting until minute 8), he shows an example of using (color) design and Gestalt principles to make equations more easily processable. The rest of the talk discusses viusally explaining machine learning.

• Datastori.es - by Enrico Bertini and Moritz Stefaner - https://datastori.es
• Data viz today - by Alli Torban - https://dataviztoday.com 

• The Data Visualisation Society - https://www.datavisualizationsociety.org - Free memberships available, great source of information and connection
• Elevate - https://www.elevatedataviz.com - Paid program at $10/month to be coached / mentored in data vis. Free content also available.