Encyclopedia of Color Science and Technology

Living Edition
| Editors: Ronnier Luo

Mesoamerican Color Survey Digital Archive

  • Kimberly A. Jameson
  • Nathan A. Benjamin
  • Stephanie M. Chang
  • Prutha S. Deshpande
  • Sergio Gago
  • Ian G. Harris
  • Yang Jiao
  • Sean Tauber
Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-27851-8_375-1


The Mesoamerican Color Survey (MCS) collected color-naming and categorization data from approximately 900 speakers from each of 116 indigenous languages from regions in Mesoamerica or Central America. Analyses of these data were originally reported by Dr. Robert E. MacLaury, principal investigator of the survey. The MCS data exist as a public-access color categorization and naming digital archive, in conjunction with other color categorization data collected by MacLaury, and are available at http://colcat.calit2.uci.edu/.


Human categorization behavior is widely studied across the behavioral sciences. It underlies many cognitive functions, including concept formation, decision making, learning, and communication. Color appearance, similar to other natural categorization domains, has distinctive features or properties that vary along continuous dimensions. Semantic color categories, their formation, their best exemplars and boundaries, and the influence of these...


Mapping Task Color Naming Indigenous Language Language Family Color Categorization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.


  1. 1.
    Berlin, B., Kay, P.: Basic Color Terms: Their Universality and Evolution. University of California Press, Berkeley (1969)Google Scholar
  2. 2.
    Kay, P., Berlin, B., Maffi, L., Merrifield, W.: The World Color Survey. Center for the Study of Language and Information, Stanford (2003)Google Scholar
  3. 3.
    Kay, P., Regier, T.: Resolving the question of color naming universals. Proc. Natl. Acad. Sci. U. S. A. 100, 9085–9089 (2003)CrossRefADSGoogle Scholar
  4. 4.
    Regier, T., Kay, P., Cook, R.: Focal colors are universal after all. Proc. Natl. Acad. Sci. U. S. A. 102, 8386–8391 (2005)CrossRefADSGoogle Scholar
  5. 5.
    Lindsey, D.T., Brown, A.M.: Universality of color names. Proc. Natl. Acad. Sci. U. S. A. 103, 16609–16613 (2006)CrossRefADSGoogle Scholar
  6. 6.
    Lindsey, D.T., Brown, A.M.: World color survey color naming reveals universal motifs and their within-language diversity. Proc. Natl. Acad. Sci. U. S. A. 106, 19785–19790 (2009)CrossRefGoogle Scholar
  7. 7.
    Kay, P., Regier, T.: Color naming universals: the case of Berinmo. Cognition 102, 289–298 (2007)CrossRefGoogle Scholar
  8. 8.
    Davidoff, J., Davies, I.R.L., Roberson, D.: Color categories in a stone-age tribe. Nature 398, 203–204 (1999)CrossRefADSGoogle Scholar
  9. 9.
    Roberson, D., Davies, I.R.L., Davidoff, J.: Color categories are not universal: replications and new evidence from a stone age culture. J. Exp. Psychol. Gen. 129, 369–398 (2000)CrossRefGoogle Scholar
  10. 10.
    Roberson, D., Hanley, J.R.: Color categories vary with language after all. Curr. Biol. 17, 605–606 (2007)CrossRefGoogle Scholar
  11. 11.
    MacLaury, R.E.: Color-category evolution and shuswap yellow-with-green. Am. Anthropol. 89(1), 107–124 (1987)CrossRefGoogle Scholar
  12. 12.
    Paramei, G.V.: Singing the Russian blues: an argument for culturally basic color terms. Cross-Cult. Res. 39(1), 10–38 (2005)CrossRefGoogle Scholar
  13. 13.
    Dedrick, D.: Color language universality and evolution: on the explanation for basic color terms. Philos. Psychol. 9(4), 497–524 (1996)CrossRefGoogle Scholar
  14. 14.
    Jameson, K.A.: Culture and cognition: what is universal about the representation of color experience? J. Cogn. Cult. 5(3–4), 293–347 (2005)CrossRefGoogle Scholar
  15. 15.
    Alvarado, N., Jameson, K.A.: Confidence judgments and color category best exemplar salience. Cross-Cult. Res. 39(2), 134–158 (2005)CrossRefGoogle Scholar
  16. 16.
    Jameson, K.A.: Why GRUE? An interpoint-distance model analysis of composite color categories. Cross-Cult. Res. 39(2), 159–194 (2005)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Jameson, K.A.: Where in the world color survey is the support for the hering primaries as the basis for color categorization? In: Cohen, J., Matthen, M. (eds.) Color Ontology and Color Science, pp. 179–202. The MIT Press, Cambridge (2010)CrossRefGoogle Scholar
  18. 18.
    Davies, I.R.L., Corbett, G.G.: A cross-cultural study of color grouping: evidence for weak linguistic relativity. Br. J. Psychol. 88(3), 493–517 (1997)CrossRefGoogle Scholar
  19. 19.
    Komarova, N.L., Jameson, K.A.: A quantitative theory of human color choices. PLoS One 8(2), e55986 (2013). doi:10.1371/journal.pone.0055986CrossRefADSGoogle Scholar
  20. 20.
    Bimler, D.: Are color categories innate or internalized? Hypotheses and implications. J. Cogn. Cult. 5(3), 265–292 (2005)CrossRefGoogle Scholar
  21. 21.
    Bimler, D.: From color naming to a language space: an analysis of data from the world color survey. J. Cogn. Cult. 7(3), 173–199 (2007)CrossRefGoogle Scholar
  22. 22.
    Bimler, D., Uusküla, M.: Clothed in triple blues: sorting out the Italian blues. J. Opt. Soc. Am. A 31, A332–A340 (2014)CrossRefADSGoogle Scholar
  23. 23.
    Narens, L., Jameson, K.A., Komarova, N.L., Tauber, S.: Language, categorization, and convention. Adv. Complex Syst. 15(03n04), 1150022 (2012)MathSciNetCrossRefGoogle Scholar
  24. 24.
    Jameson, K.A., Komarova, N.L.: Evolutionary models of color categorization. I. Population categorization systems based on normal and dichromat observers. J. Opt. Soc. Am. A, 26(6), 1414–1423. Featured Reprint in The Virtual J. Biomed. Opt. 4(8), (2009)Google Scholar
  25. 25.
    Jameson, K.A., Komarova, N.L:. Evolutionary models of color categorization. II. Realistic observer models and population heterogeneity. J. Opt. Soc. Am. A, 26(6), 1424–1436. Featured Reprint in The Virtual J. Biomed. Opt. 4(8), (2009)Google Scholar
  26. 26.
    Komarova, N.L., Jameson, K.A.: Population heterogeneity and color stimulus heterogeneity in agent–based color categorization. J. Theor. Biol. 253, 680–700 (2008)MathSciNetCrossRefGoogle Scholar
  27. 27.
    Komarova, N.L., Jameson, K.A., Narens, L.: Evolutionary models of color categorization based on discrimination. J. Math. Psychol. 51, 359–382 (2007)zbMATHMathSciNetCrossRefGoogle Scholar
  28. 28.
    MacLaury, R.E.: Color and Cognition in Mesoamerica: Constructing Categories as Vantages. University of Texas Press, Austin (1997)Google Scholar
  29. 29.
    MacLaury, R.E.: Color in mesoamerica. Vol. 1: a theory of composite categorization. Doctoral dissertation. University of California, Berkeley. UMI University Microfilms, No. 8718073, Ann Arbor (1986)Google Scholar
  30. 30.
    MacLaury, R.E.: From brightness to hue: an explanatory model of color category evolution. Curr. Anthropol. 33(2), 137–186 (1992)CrossRefGoogle Scholar
  31. 31.
    Regier, T., Kay, P., Khetarpal, N.: Color naming and the shape of color space. Language 85, 884–892 (2009)CrossRefGoogle Scholar
  32. 32.
    Webster, M., Kay, P.: Individual and population differences in focal colors. In: MacLaury, R., Paramei, G., Dedrick, D. (eds.) Anthropology of Color, pp. 29–53. John Benjamins, Amsterdam (2007)CrossRefGoogle Scholar
  33. 33.
    Paul, L.M., Simons, G.F., Fennig, C.D. (eds.).: Ethnologue: Languages of the World, Eighteenth edition. Dallas, Texas: SIL International. Online version: http://www.ethnologue.com (2015)
  34. 34.
    Jameson, K.A., Gago, S., Deshpande, P.S., Benjamin, N.A., Chang, S.M., Tauber, S., Jiao, Y., Harris, I.G., Xiang, Z., Bhakta, H.R., MacLaury, R.E.: The Robert E. MacLaury Color Categorization (ColCat) Digital Archive. http://colcat.calit2.uci.edu/. The California Institute for Telecommunications and Information Technology (Calit2), UC Irvine (2015)

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Kimberly A. Jameson
    • 1
  • Nathan A. Benjamin
    • 2
  • Stephanie M. Chang
    • 2
  • Prutha S. Deshpande
    • 3
  • Sergio Gago
    • 5
  • Ian G. Harris
    • 4
  • Yang Jiao
    • 4
  • Sean Tauber
    • 1
  1. 1.Institute for Mathematical Behavioral SciencesUniversity of California, IrvineIrvineUSA
  2. 2.Calit2, Computer ScienceUniversity of California, IrvineIrvineUSA
  3. 3.Cognitive SciencesUniversity of CaliforniaIrvineUSA
  4. 4.Computer ScienceUniversity of CaliforniaIrvineUSA
  5. 5.Calit2, School of EngineeringUniversity of California, IrvineIrvineUSA