Colour Naming: Linking Vision, Speech and Data Science

Colour Naming: Linking Vision, Speech and Data Science

Synonyms of colour words in English (in Mylonas, Koliousis & Uusküla, AIC 2021). The colour and location of the discs correspond to the coordinates of the centroids of lexical colour categories. The grey lines between the discs link colour categories that share common colour samples. The width of the lines indicates the degree of near synonymy between pairs of colour categories. The size of the discs corresponds to their frequency in the online colour naming experiment at

by Dimitris Mylonas

Colour naming refers to our intriguing cognitive capacity to group millions of discriminable colours into a smaller set of categories named, for example, “yellow”, “turquoise” or “navy”. Colour names are used to describe regions of the colour space with empirical significance and play an important role in identifying coloured objects under various viewing conditions.

In 2009, we launched an ongoing crowdsourcing study where thousands of volunteers named freely a large number of colours covering both surface and interior regions of the colour space. Over the past 12 years, we showed that web-based experimental methodologies offer considerable advantages over conservative methods in obtaining hundreds of thousands of responses from thousands of participants to facilitate colour communication within and across different languages.

Recently, we discovered that colour naming has also great educational value for engaging students of the humanities in data science methods. For example, we used data from the aforementioned colour naming experiment to design exercises for learning how to program with data in Python by (i) counting and visualising the frequency of common colour names in Newton’s Opticks and Goethe’s Theory of Colour; (ii) building colour language games; and (iii) visualising the differences between supervised and unsupervised machine learning approaches to group similar colours on the Mercator of the Munsell solid. Student progress is exemplary and we incorporated these colour naming methods in our under- and post-graduate data science courses. New research-inspired exercises, such as quantifying and visualising the degree of colour synonyms shown in the figure, will be hand-picked and integrated along the way.

Colour naming links vision and speech but can also create an appetite for learning data science.


Dimitris Mylonas is a committee member of the Colour Group (GB) and Chair of the Study Group on the Language of Colour of the AIC. He is Assistant Professor in Computer Science and Course Leader of Data Science at New College of the Humanities London at Northeastern University. His research focuses on cognitive aspects of colour. You can participate to his multilingual online colour naming experiment at

If you are a member of the Colour Group (GB) and would like to contribute a guest blog suitable for a general audience on the subject of colour, please contact