We’ve likely all seen maps of languages, though most of us don’t necessarily think about where they come from—or what they really mean. As noted in a previous GoGeomatics article from 2022, languages are important and interesting topics for the geospatially-inclined, as they can tell us a lot about a place, its people, and its history.

When we say language in this article, we specifically refer to languages humans speak, such as Swahili, Turkish, Mayan, or English. This definition may seem redundant at first, but in a digital age it is important we distinguish between languages people speak and machine languages—especially given that a map of geographic spaces is just one example of any number of forms a map can take. Think of conceptual maps, mind maps, and so forth.

An early map depicting writing systems on the African continent (Hensel, 1741)

Why maps matter when analyzing languages

Generally speaking, maps are excellent ways of condensing large amounts of complex linguistic information into formats that are easy to understand and draw people in, regardless of where they come from or what they studied in school (Upton, 2010).

To avoid ambiguity, “language map” is often used as a catch-all term for maps that attempt to reflect linguistic realities about a particular place or idea. Some types of language maps include:

• Linguistic maps, which display structural information such as speech sounds or word choices across dialects (e.g., “pop” vs. “soda” in the United States).
• Language distribution maps, which show where different languages are spoken, from particular neighbourhoods to across the globe.

While many maps can show how languages are distributed over a given area (e.g., languages of New York), they can extend beyond storytelling and data visualization to perform additional functions, such as a language learning tool for students (e.g., Algonquian Linguistic Atlas).

A language distribution map created using Voronoi polygons in QGIS (Stone & Anonby, 2019)

Despite the precise terminology we see here (linguists love definitions, after all), this doesn’t necessarily mean that linguists have read their cartography textbooks when they start putting their data on the map. And because of their powerful ability to communicate ideas, a lack of awareness of established cartographic techniques can lead to some unintended consequences. Many of these unintended consequences can happen because what we are looking at is not quite what it seems:

Language maps are not exactly maps of languages or linguistic information.
They are maps of speakers who hold the knowledge of one or more languages of interest.

(Thun, 2010)

Furthermore, unlike photographs that can show all things within a certain field of view, maps are selective by default, and show a subset of information, selected by the mapmakers (Wikle & Bailey, 2010). Very broadly speaking, we can think of two main risks associated with the language mapping process:

1. Speakers get over-represented
2. Speakers get under-represented

Some common mapping mistakes and their consequences

• Incorrect boundary types (discrete when continuous is required, graded when discrete is required). Readers may assume that a language is only spoken on one side of a boundary, or assume that there are no language varieties spoken in the vicinity of that border that include elements of the nearby varieties explicitly mentioned. This means communities of minority language speakers may not end up on the map or get recognized.
• Showing only one language per place. The number of multilingual regions outweighs the number truly monolingual regions, and displaying only one language per place (without a commentary explaining why one language per region is the focus) suggests to readers a region’s lack of linguistic diversity.
• Relying solely on secondary sources of information. The accuracy of language maps is reflected in the process of mapmaking, not simply the finished product. Language contexts can change quickly, and existing information may be outdated if it is not updated consistently or live. As language is a deeply social phenomenon, each reader and informant will have their own opinion of what is shown on the map. It’s important to have varied and multiple inputs that can be vetted. The process of doing this varies greatly depending on what you are mapping and who you are working with—and as the title of this article suggests—may be as fine-tuned as inviting knowledge holders to sketch the shape of language regions on a napkin over coffee!
• Uneven colour palettes. Data can appear more prominent when depicted using more saturated or “dominant” colours (Johnson, 2001), such as red, especially when beside less outstanding colours, such as beige. Colours can also resonate with readers on an emotional level, and mapmakers should take care when depicting one language as a cool green (for example) while another is shown in an electric pink. Similarly, some colour schemes may affect the ability for those with colour blindness to distinguish between languages, and some colour differences evident on a computer screen become obscured when printed physically. Thankfully, user-friendly guidance already exists that greatly reduces this issue.
• Inappropriate projection system. While this is by no means unique to language mapping, different projection choices affect how languages are distributed on a map. Depending on the projection system, one map could display speaker communities spread far apart, while another using the same data may suggest clustered populations (Ormeling, 2010).

Since a lack of guidelines for language mapping was noted in 2022, a systematic means of addressing these common issues has since been developed that aims to reduce these problems by cultivating reflective self-awareness among linguists engaged in mapmaking. The Evaluative Language Mapping Typology (or ELM-T) is a published document that provides a means of deconstructing existing language maps and isolating their specific components, and also acts as a list of important features and factors to account for in language mapmaking.

While this typology feels like a good foray into addressing these issues in language mapping, there is ample room for expansion beyond the academic sphere and into the geospatial community, where mapmaking experts can work alongside linguists and all others involved in the mapping process to strengthen these guidelines and language mapmaking overall.

References:

Hensel, G. (1741). Africa poly-glotta scribendi modos gentium exhibens: Charts of Aethiopic (Ge’ez) and Coptic scripts [map]. (no scale). Synopsis universae philologiae: in qua miranda unitas et harmonia linguarum totius orbis terrarum occulta e literarum, syllabarum, vocumque natura & recessibus eruitur: cum grammatica LL. orient. harmonica synoptice tractata… [Synopsis of the philology, in which a remarkable unity and harmony all the languages of the world is hidden from letters, syllables, or words. Nature recessions rescued with grammar. Orient. harmonics synoptice treated…] In commissis apud heredes Homannianos.

Ormeling, F. (2010). 2. Visualizing geographic space: The nature of maps. In A. Lameli, R. Kehrein, & S. Rabanus (Eds.), Language and space, Volume 2: Language mapping (pp. 21–43). De Gruyter Mouton.

Johnson, J. M. (2001). Mapping ethnicity: Color use in depicting ethnic distribution. Cartographic Perspectives, (40), 12–31.

Stone, A. & Anonby, E. J. (2019). Figure 14: Static polygon representation of language distribution in Chahar Mahal va Bakhtiari Province [map]. In E. Anonby, M. Taheri-Ardali, & A. Hayes. The Atlas of the Languages of Iran (ALI): A Research Overview. Iranian Studies.

Thun, H. (2010). Pluridimensional cartography. In A. Lameli, R. Kehrein, & S. Rabanus (Eds.), Language and space, Volume 2: Language mapping (pp. 506–523). De Gruyter Mouton.

Upton, C. (2010). 7. Designing maps for non-linguists. In A. Lameli, R. Kehrein, & S. Rabanus (Eds.), Language and space, Volume 2: Language mapping (pp. 142–166). De Gruyter Mouton.

Wikle, T. A. & Bailey, G. (2010). Mapping North American English. In A. Lameli, R. Kehrein, & S. Rabanus (Eds.), Language and space, Volume 2: Language mapping (pp. 253–280). De Gruyter Mouton.