Robert E. MacLaury Color Survey

Welcome to the Color Categorization (ColCat) Digital Archive!

The ColCat Wiki is the place where color categorization data from a wide variety of languages and dialects can be examined, downloaded, searched, and queried for the purpose of non-commercial research on color cognition and language across language groups. It is a public-access platform created to make available unpublished raw data sets from Dr. Robert E. MacLaury's Color Categorization Archive and other contributed color categorization datasets.

The aim of the ColCat Wiki is to provide a collaborative research platform for investigating human color categorization behaviors across ethnolinguistic groups. 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 on human behavior, have been topics of much empirical study, receiving considerable attention from anthropologist, linguists, cognitive scientists and psychologists. The general aim of such research is to understand human color categorization and how it is cognitively and culturally represented across languages. For the case of color categories, the literature suggests that there are “universal trends” in human color representations with category best-exemplars being predictable across languages, and there are culturally-specific color categorization influences, as well as human evidence and simulated color category evolution evidence suggesting combinations of universal, cultural and pragmatic influences on color categorization and naming behaviors.

The Robert E. MacLaury Color Categorization Archive

The Robert E. MacLaury Color Categorization Archive consists of all raw ethnolinguistic survey data collected as part of Rob's nearly 30 year research program. It includes two distinct color surveys, namely, The Mesoamerican Color Survey and MacLaury's Multinational Color Survey. Both surveys employed standardized color "Naming" and category "Focus" tasks, similar to those used in the World Color Survey (http://www1.icsi.berkeley.edu/wcs/), and many of MacLaury's surveys additionally include category "Mapping" tasks that capture the denotative range data for color terms elicited from surveyed participants.

MacLaury's Mesoamerican Color Survey:

The Mesoamerican Color Survey was conducted by MacLaury between the years 1978 to 1981. It includes interviews with 900 speakers of some 116 Mesoamerican languages/dialects in which color categorization behaviors were collected with a standardized method similar to that used in the World Color Survey (Kay, Berlin, Maffi, Merrifield and Cook 2010; Link). MacLaury's 1997 book on the MCS survey (Link ) provides a sweeping overview of the organization and semantics of color categorization in modern Mesoamerica from the point of view of Vantage Theory. The raw data files of MacLaury's MCS survey are made publicly available on the ColCat site for the first time.

The Mesoamerican Color Survey (MCS) is one of two existing databases (the other being the World Color Survey, or WCS) which directly investigated, on a large scale, color naming and categorization across many linguistic societies. The MCS and the WCS employ nearly identical standardized procedures for evaluating large numbers of color stimuli, languages and informants. MCS data were collected by MacLaury himself, or by research associates and colleagues in Mesoamerica who MacLaury trained and directed. It is estimated that more than 100 indigenous languages are spoken in Mexico and Central America. Like most languages each MCS language has a color lexicon that partitions environmental color appearance stimuli according to a pattern that is specifically relevant to a given language’s speakers. But every local MCS system of color categorization also shares characteristics with systems observed for other Mesoamerican languages and with those of languages elsewhere in the world. MacLaury published analyses of the MCS data in the context of his Vantage Theory modeling approach (MacLaury, 1997).

MacLaury's Multinational Color Survey:

In addition to the Mesoamerican Color Survey, MacLaury collected color categorization data on languages from a variety of locations across Africa, Europe, The Americas, Asia, and elsewhere. These data are provided here as the Multinational Color Survey portion of the MacLaury archive, and represent 92 additional surveys. Neither the raw MCS data nor the MacLaury multinational language surveys have been systematically organized for public use or previously made available in unanalyzed form. The additional Multinational color categorization surveys (some with only a single informant, while others have as many as 40 informants) are valuable for their diversity in that they include native speakers from a wide range of languages including several Slavic languages, Hungarian, several Salishian languages of the Pacific Northwest United States, Zulu and several other South Africa/Zimbabwe languages, native American languages, Germanic languages, European languages, Asian languages, and more.

How to Contribute

1. Create an account to gain access to the language data archives and research tools.


2. Download data from the language archives, transcribe, discover, and publish.


3. Contact colcat@calit2.uci.edu with transcriptions and publications you would like to contribute to the website.

UC Irvine ColCat Color Categorization Surveys

Check back for new downloads of other color categorization datasets contributed by researchers from UC Irvine, and from other universities.

Download the ColCat Wiki Terms and Conditions of Use (.pdf)

Download the ColCat Wiki User Documentation (.pdf)

Instructions from MacLaury to field researchers (.pdf)

List of surveys and investigators in the MacLaury database (.pdf)