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The lay of the language: surveying the cartographic characteristics of language maps.


Among the many staple figures found in introductory human or cultural geography textbooks, language maps are consistently used as illustrations for lessons on linguistic and cultural diversity. For some students, the single image of a language map can convey ideas of cultural distribution and migration that may outpace the effectiveness of written passages on the same topics. However, language maps cannot perfectly capture the true linguistic environment of a study area. They require considerable generalization given the fluidity of languages. Language maps are simply generalized snapshots in time of a variable that is in constant change. Further, some of these maps can be confusing to interpret. When no information is provided about data or design decisions made in producing the map, the message presented to users can be vague or even conflicting. These confusing figures, often found in educational contexts, generated our curiosity about language map construction.

Unlike other disciplines with ongoing discussions of standards and guidelines for mapping (e.g. geology), an important revelation about language mapping is that there are no established standards or rules to guide language map construction (Kirk, Sanderson, and Widdowson 1985; Ambrose and Williams 1991; Williams 1996). This absence of common conventions is especially problematic since language mapping is used in many disciplines including geography, linguistics, and anthropology. With researchers from diverse disciplines approaching the task of language mapping with their widely varying expertise, some construction guidance would be useful to produce a level of consistency within the map genre. Further, the lack of guidelines does not indicate a lack of difficulty in producing language maps. Language is dynamic and often intangible, which are not qualities that make cartographic representation an easy assignment. In fact, the translation from a language dataset to a language map produces a number of conceptual cartographic issues that can result in misrepresenting the language reality. The vector format predominates in language mapping although the use of discrete points, lines, and polygons is not a natural fit to the nature of language. Language is described in the literature as fluid and continuous, characteristics that oppose the qualities inherent in vector mapping. Determining and depicting language boundaries as solid lines does not reflect the existence of language transition zones described by researchers. Similarly, the common trend of showing only one language per place does not convey the reality of linguistic diversity and plurality, which is a common feature of contemporary society. For reasons of confidentiality, language data are frequently aggregated when used for mapping purposes. To achieve this, political mapping units such as countries or states are sometimes used as language mapping units although language may not naturally function at these scales. All of these issues, related to making language fit the mold of a vector environment, can compound to thoroughly disguise the real nature of the language landscape.

With a frequent language loss and language movement occurring in our world today, language maps will continue to be useful tools for both research and educational purposes. Fortunately, we now have new technology available to tackle some of their construction problems. Geographic information systems (GIS) allow for increased flexibility in data storage, manipulation, analysis, and display that far outpaces previous technology. The introduction of GIS can breathe new life into the task of language mapping, renewing it as a field ripe for research. However, where do we begin? What types of maps and design elements do language maps typically feature? Without commonly held conventions, it is unclear what symbology strategies are used most often in language mapping and therefore what strategies we should review and potentially improve. Only Ambrose and Williams (1991) attempt to provide a general typology of language mapping trends; however, their symbology summary is not accompanied by any quantification of formal map observations. Over twenty years after the publication of Ambrose and Williams (1991), we follow up on their work by applying their symbology typology in a quantified map survey to document the characteristics of language maps. We characterize language-mapping practices by surveying the cartographic qualities of existing language maps, extracting patterns of language map construction from the trends observed in a sample collection of maps. This map survey addresses two questions: (1) what are the common cartographic characteristics of language maps; and (2) does the existing general symbology typology of Ambrose and Williams (1991) adequately capture language mapping in practice?

Related work

Language mapping is not a new endeavor. Publication of linguistic atlases created from extensive survey research began most notably in Europe in the late nineteenth century with works focused on Germany and France (Crystal 1997). The undertaking of such large, linguistic surveys created many challenges long before reaching the actual mapping stage of the project. Researchers had to choose representative communities and individuals for their samples; compile questionnaires that captured appropriate features; develop fieldwork methods and train fieldworkers; verify data; and, of course, obtain financing (Kurath 1931 ; Menner 1933; Mackey 1988; Williams 1996). Numerous researchers provide detailed documentation of language mapping and linguistic atlas history as well as thorough descriptions of individual atlas projects (Kahane 1941; O'Cain 1979; McDavid et al. 1986; Pederson 1993; Crystal 1997: Wikle and Bailey 2010).

Language maps as a whole are a thematic map genre that features great variety in both the use of different symbology options and the display of different data variables. Both Ambrose and Williams (1991) and Ormeling (1992) provide general descriptions of symbology types used for language maps. Ormeling (1992) discusses the use of chorochromatic, choropleth, isoline, and flow line maps for linguistic data as well as proportional and qualitative symbols. Ambrose and Williams (1991) provide a visual aid for their symbology summary and categorize mapping techniques by the use of points, lines, and polygons (Figure 1). For the most part, these language mapping overviews reiterate commonly known cartographic techniques. Only one symbology type, the use of isoglosses, is unique to language maps. Unlike the isoline, which connects points of equal value (e.g. elevation contours; Gregory et al. 2009), an isogloss is a boundary line that defines areas where the use of a particular linguistic feature is different (Finch 2000; From kin and Rodman 2002; Crystal 2005). An isogloss may note areas that differ in the pronunciation of a word or that use a different word for a specific item. When multiple isoglosses spatially coincide or bundle up, it can potentially indicate the location of a dialect boundary (Kurath 1931; Wagner 1958; Masica 1976; Breton 1991; Finch 2000). Concerning variables, there is no shortage of displayed data variety for language maps. Linguistic atlases feature the spatial distribution of internal or sublanguage characteristics such as pronunciation, vocabulary, and structural features. Conversely, other maps depict characteristics that apply to languages as a whole such as the distribution of language families, language areas, or official languages, as well as speaker percentages or rates of bilingualism. While the terms "language map" and "linguistic map" are used interchangeably in the literature, we use the general term "language map" in this article to refer to any map that features some kind of language data as its focus.

As mentioned above, language mapping is still without a set of standards for map construction (Kirk, Sanderson, and Widdowson 1985; Ambrose and Williams 1991; Williams 1996). This absence of guidelines, however, has not decreased the presence of language maps, especially those found in textbooks. Recent editions of college-level introductory geography textbooks still feature one or more language maps within their covers (e.g. Fouberg, Murphy, and de Blij 2009; Dahlman, Renwick, and Bergman 2010; Getis et al. 2010; Knox and Marston 2010; Marston et al. 2010; Rubenstein 2010). Although the commonly featured map of the world's languages is an intentionally generalized depiction of language distribution, Mackey (1988) states that it is oversimplified while Brougham (1986) finds the structure outdated. The main issues that arise in language mapping are related to the use of a vector environment. Both Ormeling (1992) and Ambrose and Williams (1991) predominantly speak of vector symbology types using points, lines, and polygons in their discussions of language-mapping symbology. While the vector format prevails in language mapping, it contrasts strongly with the continuous nature of its subject (Breton 1991). The result of this conflict is the loss of a key characteristic of the language reality when translated to its cartographic representation. The use of a vector format for language map construction creates three main issues: boundary representation, choice of mapping units, and display of linguistic plurality.

The placement and depiction of boundaries can be difficult for almost any mapped variable; however, boundaries on language maps pose their own additional challenges. The location of lines on language maps can result from arbitrary decisions (Macaulay 1985). In the case of isogloss mapping in particular, lines are drawn based on researchers' decisions about the location of observed data points (Kirk, Sanderson, and Widdowson 1985; Ormeling 1992). Given this interpretive aspect of isogloss depiction, the same dataset used by different researchers can produce different boundary results (Onneling 1992). Further, resulting boundaries are contingent on the particular data that are collected (Mackey 1988; Davis 2000). Collecting different linguistic features can produce different dialect boundaries (Davis 2000)just as collecting different measures of language use can produce different language boundaries (Williams and Ambrose 1988). Williams and Ambrose (1988) note that there is no widespread agreement as to what aspect of transition a language boundary should represent. Every different method used for positioning a language boundary can create different spatial characteristics, so one should exhibit caution when interpreting the potential significance of such boundaries on a map. Besides the difficulty of the placement of language boundaries is the issue of whether discrete boundary lines are even appropriate for language data. Lines convey a level of data precision and confidence beyond what is true (Williams 1996) and in general are incapable of conveying the extent of processes and events that occur at contemporary language boundaries (Williams and Ambrose 1988). Rather than language boundaries or abrupt transitions, the literature repeatedly mentions border areas, transition zones, or transition belts (Hall 1949; Kirk, Sanderson, and Widdowson 1985; Masica 1976; Breton 1991; Ormeling 1992). These transition zones or "linguatones" (Luebbering 2011) can cover large areas containing converging language systems and complicated structures (Kirk, Sanderson, and Widdowson 1985; Breton 1991). The use of lines to represent such transitions disguises their true character and complexity.

The selection of mapping units is another integral decision for all map projects that again takes on further considerations when dealing with language data. Ambrose and Williams (1991) attest that in the case of language mapping, the choice of mapping unit is not given enough thoughtful consideration. In the case of language mapping, however, the possible mapping unit candidates are often all less than ideal. Language occurs at the level of an individual, but due to efforts to maintain confidentiality and anonymity as well as the challenge of assigning a specific location to a nonstationary individual, language data are often aggregated or collected at an aggregated scale. This results in the use of areal units to represent a phenomenon that occurs at the level of the individual speaker. While this scenario is already problematic, the type of areal units used can further compound the problem. Administrative units, such as countries, states, or census geography units, are often employed on language maps (Williams 1996). Such units have boundaries that are at times formed arbitrarily, may change considerably over time, and vary in size with rather irregular shapes (Ambrose and Williams 1991). Language falsely appears as completely homogenous within these ill-suited, politically-based mapping units (Ormeling 1992; Williams 1996).

The issues in using a vector map format for language mapping are further revealed when trying to handle the linguistic plurality prevalent in today's world. Frequently in language mapping, only one language is assigned per mapping unit. Such monolingual mapping however is a mismatch for the multilingual residents of many places in the world. In order to map a multilingual society with monolingual polygons, decisions are made as to whose language will be assigned to a mapping unit--whose language will be visible and whose will not. This element of language map compilation reveals the problem of power and perception that can accompany language maps. The limitations of map symbology problematically confront the power struggles among languages, and the cartographer, in a way, must take sides (Breton 1992). In choosing one language to represent an area (e.g. official language or mother tongue), the cartographer is favoring one population while others are left unrepresented and marginalized, masking the true linguistic diversity of the area (Breton 1992). The world language maps found in textbooks and atlases undermine languages that do not have official recognition by spatially exaggerating the state languages that do (Williams and Ambrose 1992). The placement of language boundaries and labeling of language areas can be highly contentious and can influence political policy and its potential beneficiaries (Williams and Ambrose 1992; Williams 1996). The compromises that must be made to balance the dominant relationships among languages with map symbology limitations can result in a map message that misleads map users. Add to this scenario the personal expectations for language representation of the map viewer, and as Peeters (1992) notes, a single language map is never able to appease all of its users nor can it display all information of importance.

As evidenced by the publication years of the sources discussed above, language mapping issues were predominantly researched in the 1980s and 1990s, while current research on the topic has dwindled. Interestingly, research on the cartographic complications of language mapping declined rather simultaneously with the growth of GIS, the best available tool to date for tackling such issues. The potential use of GIS with linguistic datasets is hailed by researchers (Williams and Ambrose 1992; Lee and Kretzschmar 1993; Williams 1996; Williams and Van der Merwe 1996; Kretzschmar 1997), yet GIS has made few appearances in geolinguistic research (Hoch and Hayes 2010). Lee and Kretzschmar (1993) discuss spatial analysis possibilities for GIS with linguistic data, while Wikle (1997) explores language data visualizations with quantitative maps. Kretzschmar (1997) investigates spatial autocorrelation and density estimation for linguistic features. All of this work, however, is over 10 years old. Great advances in GIS technology have been made since these publications, so not only are there multiple avenues for new research, but even these early GIS efforts could be reproduced now with different results given today's technology. GIS provides the opportunity to improve language mapping, but perhaps the best evidence to help us guide future efforts is a thorough review of what has succeeded and failed in the past. Recent research provides general overviews of language mapping problems, history, and suggestions for future work (Hoch and Hayes 2010; Wikle and Bailey 2010; Luebbering 2011), but none of these works provide concrete data on language map characteristics. We have no common language mapping conventions at our disposal, nor has there been any systematic research documenting language mapping trends. In an effort to fill this research gap, we have conducted a survey of language map characteristics as a means of quantifying language mapping patterns as well as helping to identify areas for improvement. By observing the design elements of language maps produced over the years, we are able to identify the common practices of language mapping from the maps themselves.


Collection of map sample

We first collected language maps to form the map sample for our survey. Stemming from the original motivation for this research, we began our search for language maps with those found in geography textbooks. Next, we conducted library and journal database searches, internet queries for images and websites, and manually reviewed atlases in the Virginia Tech library. However, language maps are often not standalone products and can be found within works not focused solely on language. Often it requires some familiarity to know of and locate a particular language map. For example, a language map could be a figure in an article within an edited book about a particular culture. To locate more language maps, and specifically ones that are in use, email queries asking for language map references were sent to three professional listservs for cultural geographers, linguistic anthropologists, and linguists. Potential respondents were informed that there were no limitations of specific regions, languages of interest, publication date, data type, or presentation format. Any language maps encountered or used in teaching, research, or one's own reading were of interest. We received over 50 responses to these queries. In addition to the language maps suggested by respondents, the listserv replies often led to other potential language maps based on the sources of their suggestions.

While some works contained only one language map, others contained multiple maps and required a sampling strategy for determining which to survey. If all the language maps in a source were similarly constructed (e.g. a language atlas with one uniform mapping type used for each geographic area), only one language map was surveyed. In selecting the map to survey, we chose the most complicated map in terms of number of data items, data hierarchy levels, and spatial proximity of mapped languages. The purpose of choosing the most complicated map was to survey the full extent of how that particular mapping strategy was used. A map showing only two languages that never spatially coalesce does not indicate how the mapmaker deals with overlapping languages; a map showing five adjacent or overlapping languages and dialects reveals more about the data and display decisions made in construction of the map. If a source contained more than one type of language map symbology, one map of each type was surveyed, again choosing the most complicated map example for each in order to capture all of the design elements used for that particular map type. The intention of this research is to discover the different types of cartographic representations of linguistic information that are used, not to proportionally represent the language map types from a source. For example, if a book contained 20 language maps with proportional circles and one choropleth language map, we would survey one proportional circle map and the one choropleth map. This methodology helps to capture the diversity of language mapping strategies as well as prevent survey redundancy of a source. If we surveyed language map types in proportion to their occurrence in a source, we would redundantly sample the most prominent language map types more than once, providing no new information and skewing our language map type results in favor of works with multiple maps of the same type.

Language map sample limitations

Two types of language or language-related maps were not included in this survey. First, maps depicting toponyms were not included. Toponyms are place names; they are language labels for places (Norton 2010). Although toponym maps are related to language and can help indicate the past or current presence of different cultural groups, they are examples of language used to label a place, not an instance of specifically depicting the spatial distribution of a language or language feature. Language diffusion maps were also excluded from the survey. Diffusion maps attempt to depict language movement and dispersal and therefore have different intended messages and symbology needs than maps showing static language locations and distributions. Typically in diffusion maps, scaled, directional arrows indicate the general progression of language without defining specific paths of movement or destinations. These indefinite depictions of the spatial movement of language do not have the same construction issues with map unit choice, boundary depiction, or showing linguistic diversity as do nondiffusion language maps. They were therefore excluded from this survey to be the focus of a future research endeavor.

Additional sample restrictions helped to ensure the quality of our map sample and interpretation of map components. Maps produced in languages other than English were included in the survey on a case-by-case basis. Since the overall map symbology and design elements are of interest rather than the specific mapped elements (such as language or dialect names), non-English maps were surveyed, but only if their symbology strategy was clearly decipherable. If any map element was unclear, and therefore the particular function or intent unknown, the map was excluded from the survey. Any maps found posted on wiki-related or personal websites were excluded unless their original source could be obtained, or, in the case of personal websites, the authority of the author could be verified (e.g. personal website of a linguistics professor). The website types included in the survey were mainly composed of those hosted by government or nonprofit organizations, research institutes, universities or other educational institutions, and sellers of map products. If a map was noted as an adaptation of an earlier source, every effort was made to locate and survey the original language map so as to have an accurate representation of the original map construction characteristics associated with the true year of origin.

Survey components, map classification typology, and data collection and analysis

Conducting a survey of map components is not a new methodological approach for assessing map composition. Recently, Kessler and Slocum (2011) assess the quality of maps published in geography journals with a survey using both qualitative and quantitative means of commenting on and rating map features. Our survey, used to record the characteristics of each language map, did not rate maps, hut instead captured basic reference and map design information as well as aspects specific to a language theme. The collected map characteristics for the survey included among other items: full source reference, publication/outlet type, year, data source, scale, study area, map caption, language variable(s), symbology used (points, lines, polygons, or grid cells), boundary line characteristics, map unit (s), and the maximum number of languages or language items shown in one location. These survey components addressed the problematic aspects described in the literature, such as boundary representation and the visibility of linguistic diversity, and created a thorough inventory for each map.

For a summarized and consistent classification of language map symbology, the general language map symbology classification scheme of Ambrose and Williams (1991) (Figure 1) was used as a guide. The authors attest to this being a general summary for most of the symbology used for language maps; it was not intended to be comprehensive. As a result, each map in the survey was labeled with the corresponding symbology types (noted by letters) from Figure 1, with additional details noted as necessary to fully capture the map's language symbology strategy. Two symbology types in Figure 1 were excluded from use: type H, "lines indicating language dynamics on a diffusion map, and type M, "computer-generated language map". Type H was excluded since, as explained above, language diffusion maps were not included in the map sample. Type M, the computer generated map, was excluded due to its vague and outdated nature. Most, if not all, contemporary language maps are computer-generated; further, the type of computer-generated language map referred to with this symbology type (as seen in Figure 1) is an early grid-plot method that represents just one technique in the development of computer cartography. With an emphasis on specific symbology strategies, we did not distinguish or note noncomputer versus computer-generated maps. The definition of type A, "employing the written word," was not fully explained by Ambrose and Williams (1991). From our own interpretation and tying in with observations from various maps, the symbology type was expanded beyond the visual example showing the placement of vocabulary words in use in their associated map regions (Figure 1). In our survey, type A symbology refers to any map that conveys language information through labels directly on the map rather than through the map legend. Any map that features spatially placed labels with a level or specificity of language information that cannot be obtained through the map legend or other symbology is considered showing type A features.

All map survey observations were recorded on the map survey sheets. A photo, scanned image, screenshot, or downloadable online image was saved as a visual reference for each map surveyed. The survey sheet data were later recorded in an Excel spreadsheet and Access database for efficient data organizing, querying, and analysis. We tabulated and summarized the frequency of different characteristics (such as the presence/absence of scales, boundary representation, language data variable type, symbology type, etc.) using sort and query functions. We also reviewed in detail the additional notes for each map to discover features not captured by the survey or symbology typology and their relative frequency and context.


Basic map sample and design characteristics

References from listserv responses as well as the results of our own search produced a map sample of 240 maps from 150 different sources. The most maps surveyed from a single source was 12; the average number of maps surveyed per source was 1.6. Map source types included atlases, books, government publications, journal articles, map products, newspapers, organizations, textbooks, and websites. Websites and books were the most common sources, with these two categories providing almost half of the total map sample (Figure 2). Source years ranged from as early as 1741 to 2010 with a median year of 1997. Figure 3 shows the frequency distribution of publication decade for both map sources and maps. Any websites that did not indicate a date (either for its original posting or for its latest revision) were excluded from source year calculations (seven exclusions total); we did not substitute the access date.

The survey captured basic map design elements in addition to those particular to the language theme. Approximately 98% of maps were in vector format; conversely only 2% were raster. The map sample was rather evenly split between maps published in black and white versus color, 45% and 55% respectively. Only half (49%) of sampled language maps showed a map scale. Scalable maps available via web sources accounted for 4% of the map sample. Of the 47% of maps without a scale, roughly 7% did show latitude and longitude lines. Related to scale, the coverage area of the language maps included in the survey ranged from as small as a community to the extent of the world. The most frequent coverage area of the map sample was the extent of a country (almost 38%); 12% of maps encompassed the entire world (Table 1). Table 2 shows the use of points, lines, and polygons for depicting language data on the maps. Polygons were the most prominent element, seen in approximately 68% of the maps.

Language map design elements and construction issues

In reviewing the 240 maps, the specific content of the language theme varied considerably, with many different language variables observed. We summarized the different language information found in the map sample into general categories (Table 3). Languages themselves were the most common map variable (e.g. map showing the languages of Europe), found on 37% of maps. Following in occurrence were language features (e.g. accents, dialects, word usage, vocabulary), which appeared on approximately 33% of maps, language relationships (e.g. language phylum, family, stock, branch, group) on 27%, and counts or proportions (e.g. number or percentage of language speakers) on 11% of maps. Each of the remaining categories was found on less than 10% of maps. Only 10 maps accompanied their language theme with additional nonlanguage data (not including reference layers such as administrative boundaries or cities). Additional information included items such as ethnic groups or tribes, land cover or land elevation, migration, population, and religion.

As stated in the literature, many construction issues are encountered when cartographically depicting language, particularly with boundaries, map unit choice, and handling linguistic diversity. Each of these aspects was addressed by the captured survey data. Concerning boundary depiction, of the 196 maps that used boundary lines for language-related information, 57% used solid line boundaries (Table 4). Of the 43% of maps with language-related boundary lines depicted with nonsolid patterns (e.g. dashed lines or polygon fill with no line edge), 10 maps (12% of all maps using nonsolid lines) appear to use such line patterns for visual distinction among map items rather than to reflect uncertainty or fluidity in the data (Figure 4). Map units used throughout the map sample ranged from individual observation locations to entire continents. The most common map units are listed in Table 5. "Language areas" were used in 32% of maps with the next most common unit being "language family areas", observed in 16% of maps. After categorizing map units into political and nonpolitical units (based on the units used to display language data, not units used for orientation or reference purposes), we found that 18% of maps used political units; conversely, 82% used nonpolitical (language based) units. To record how maps displayed linguistic diversity, we noted the maximum number of languages (or language features) displayed in one spot through symbology, whether through polygon shading, boundary coalescence, or labeling. First, we found that 18% of the maps in the sample showed the distribution of only one language, language feature, or language measurement (e.g. distribution of Spanish speakers). Although many of these variables either imply the presence of more than one language or language feature (e.g. if 95% of people speak English the other 5% must speak something else) or acknowledge it directly (e.g. mapping bilingualism rates), it is the variable that indicates more than one item per place, not the symbology design. After excluding those maps with singular features, 197 maps (82% of map sample) remained (Table 6). Fifty-nine percent of these maps (49% of the entire map sample) showed only one language or language item per place (Table 6). Forty-one percent of these maps (33% of entire map sample) showed more than one language or language feature in one location.

Application of Ambrose and Williams' (1991) symbology types

Using Ambrose and Williams' (1991) language symbology typology (Figure 1), we categorized the symbology types observed in the map sample. Since many maps featured more than one layer of language symbology, we used the types, indicated by letters, consecutively in alphabetical order to describe each map as needed (ex. type A or type AI). Table 7 shows the frequency of each language map symbology type as well as the most common symbology types used overall (combinations included). Types I and A were observed in 47% and 37% of the maps respectively, followed in frequency by types B (21%), E (14%), and K (13%). All other symbology types were seen in less than 10% of maps. The most common combination of symbology types in the language maps was that of type A used with type l; 17% of the map sample featured this specific symbology combination of language data labels with polygon fill colors or patterns. Concerning levels of Ambrose and Williams' typology used, the majority of the sample (57%) fell into just one symbology category, while 39% of the maps were best described by two types and 4% displayed three symbology types.

Unique strategies observed

In addition to the map qualities recorded and summarized above, we also noted any unique aspects of each map that were not captured by the standard survey components. The resulting notes provided interesting examples of map design strategies implemented to deal with the uncertainty and complexity of language data. These examples fall under three general headings: visualizing linguistic diversity, indicating data uncertainty or fluidity, and using unanchored labels.

Amidst the 33% of the map sample that showed more than one language item per location, we found a few unique methods for handling this plurality of data in one spot with symbology. Some maps that used polygons as mapping units featured a "mixed-area" legend item (Figure 5; SIL (SIL International). 2007. Languages of Nigeria. Digital file received from R. Blench). Other maps used symbology designed to visually and distinctly overlap, using either strategic polygon fill types or a combination of points and polygons (Figure 5). To deal with uncertainty, some mapmakers issued caveats with their maps about the potential issues with the depiction of language location and boundaries (Table 8). Others went beyond mere text admonitions and incorporated symbology that indicated uncertainty. Different strategies we observed included: (1) use of nonsolid boundary lines (sometimes in conjunction with solid boundary lines for more certain areas), (2) question marks integrated with labels and boundary lines, (3) a zipper-like boundary transition zone, and (4) use of an "unknown" category for language information (Figure 6). The final feature, unanchored labels, was observed on 17% of maps. Unanchored labels are labels on the map that are not tied to or enclosed by points, lines, or polygons (Figure 7). Such labels sometimes vary in size, orientation, and character spacing within the same map.


What began as a basic survey of language maps resulted in a substantial amount of data and findings concerning the symbology strategies and design of language maps. Although language maps were not considered simple or lacking in variety, the complexity and diversity of the language maps found was surprising. Using professional listservs proved very fruitful as we received over 50 responses from faculty and professionals in various disciplines who were eager to contribute. From this experience, it is recommended that researchers reach out to professional organizations and research group listservs when local collaborators or experts are lacking. Many of the maps suggested by listserv respondents would not have been discovered through our own map search. Additionally, the importance of, and interest in, our research was validated by the interest (of linguists in particular) in our work and eventual results.

The final sample size of 240 maps was not established due to a lack of language maps after that number, but rather observations of diminishing returns of map symbology types. As expected, language maps were found in many different publication outlets. The prevalence of language maps found on websites (25% of the sample) indicates the importance of the web for accessibility to language maps. The Internet provides a venue for web-based GIS and other interactive language map projects, but also serves as a repository for digital files of older language maps such as the scanned map images available through the Language and Location Map Annotation Project (LL-Map 2009). The source year of the earliest map in the sample (documented as 1741; Lameli 2010) predates the major early linguistic atlas efforts that took place in the late nineteenth century (Crystal 1997) and gives weight to the historical presence of spatial depictions of language. The greater frequency of language maps in more recent years in our sample is likely attributable to the familiarity with and accessibility of current publications. Our sample strategy did not aim to estimate the number of produced language maps over time, so we cannot say that language map production and use is increasing, but the sample characteristics suggest that language is still a very visible map theme. It is convenient that almost 70% of the map sample is from 1980 to present. The majority of cartographic research discussing language map visualization problems was published in the 1980s and 1990s. Therefore, the maps sampled during and after the 1980s and 1990s provide a glimpse of language map trends during and after language maps were scrutinized and critiqued by researchers.

The basic map elements of our sample predominantly matched the expectations developed from the literature. The dominance of the vector format of language maps was not a surprise due to its discussion in the literature, although its sheer magnitude (98% of our sample) was unanticipated. Maps produced in black and white versus in color are perhaps more due to the time period and requirements of publications as opposed to a specific design choice; it therefore does not reveal much about language mapping trends. The statistics on the coverage area of our language map sample shows that smaller scale maps are common; almost 30% of maps had a continental or world coverage area. Although continents and countries vary considerably in size, that 79% of maps have coverage areas at the country-level or above does indicate a general tendency for smaller scale maps. These larger coverage area maps could help account for why many maps (47%) did not feature scales. Map scale could be deemed less important for such small-scale depictions that serve as generalized reference figures. Ambrose and Williams (1981) called for the use of a variety of complementary scales, both small and large, for geographic language studies. With only 5% of maps at the city or community level, the proliferation of large-scale language map studies appears to still be lacking. The trend of polygons as the dimension of choice for language maps (68% of the map sample) is logical. The use of points requires spatial specificity, enough knowledge to pinpoint language information to one spot. Lines are also difficult as they represent possibly the most problematic aspect of representing language data on a map: boundaries. Generalizing to a polygon or area is perhaps the best way to represent something that can be fluid and inherently uncertain.

Languages were the most frequently mapped variable, but the variety of variables used in the map sample (anything from the word used for "pancake" to the endangered status of indigenous languages) really shows the data collection diversity and potential concerning language. The different levels of meaningful and interesting linguistic data translate to more mapping possibilities and varieties. If any map sample feature indicates the breadth of language mapping design and the different pieces of information language maps can convey, it's the variety of language variables observed. Although only 10 maps featured additional data accompanying the featured language information, the variety of the additional data shows how language information can complement many different datasets. Religion and ethnicity are sometimes closely related to language, with each potentially reinforcing or providing more evidence to verify the location of the other. Migration can be charted by the relatedness of languages and through changing language patterns (Dyen 1956). Some researchers have also associated biodiversity with linguistic diversity (Harmon 1996; Maffi 2005).

The use of nonsolid boundary lines for mapping language information is a simple but effective means of indicating questionable boundary accuracy or language fluidity. Forty-seven percent of the entire map sample (57% of the subset of maps featuring language boundaries), however, used solid-line boundaries. It is interesting that one of the easiest symbology amendments that can be made to convey the transitional nature of language features (or "linguatones"; Luebbering 2011) is infrequently utilized. This trend is associated with the use of political mapping units for language maps. Political mapping units are often given solid boundary lines that relate to their defined nature, so when used as the mapping units for language maps, language variables take on the appearance of those boundary lines. Some maps offer a caveat on boundaries stating their unreliability, albeit often printed in tiny italicized font in the map margin. If a mapmaker is willing to add this admonition to the map, why not also embed the idea into the symbology and use nonsolid boundary lines as well? Given that many of the maps are drawn at small scales and are obviously generalized representations of the distribution of language variables, it may be that solid boundary lines were used since the map itself is assumed to be understood by viewers as a grossly generalized representation already. For these generalized representations for general audiences, solid boundary lines may simply be chosen for visual clarity, not in an effort to feign data authority.

The literature repeatedly points to the issue of using political units as language mapping units, and we found this trend on almost one-fifth of the map sample (42 maps). Considering that the critiques of the use of political mapping units were published at least 15 years ago (Macaulay 1985; Ambrose and Williams 1991; Ormeling 1992; Williams 1996), it is surprising that their use is still so prominent. At the same time, using established mapping units and geographic summary areas speed up the organization and process of collecting and mapping information. It also provides the information in spatial units that are familiar to audiences. Since language maps are often used as educational visual aids, the use of political mapping units could be a strategic choice for some map products. Further, language is something central to our identities, and it could be that the need to maintain privacy and anonymity leads to the choice of political mapping units. If maps using political units provided an explanation of their mapping unit choice (e.g. whether that is the unit of data collection, for geographic familiarity, or for confidentiality), their use would be less problematic. With no explanation provided, the use of political mapping units for language information gives the appearance that language operates and changes at political unit boundaries.

Power with perception, as conveyed through the handling or ignoring of linguistic diversity in map symbology, is perhaps one of the more important issues to address since language maps are often educational tools. Of the maps featuring more than one language or language feature within their theme, less than half showed more than one item per place; the majority (59%) featured monolingual mapping. The prevalence of monolingual mapping could be related to the frequent use of smaller scale, larger context area maps as discussed above. These maps tend to have less complicated, more summarized information and related symbology for illustrative purposes to general audiences. The amount of information that can be clearly displayed on a map is scale-dependent, and the common occurrence of generalized small-scale maps in our sample is likely appearing through the percentage of maps showing only one item per place. Forty-one percent of maps with multiple features did show more than one feature per place. This is a sizable proportion. Without previous map samples to compare to and without including temporal analysis (the subject of future research), we have no way of noting if this is an improvement since the literature's criticism of the power struggles evident in language maps.

None of the monolingual maps make any claims to be showing everything; they do not make statements proclaiming any authority. However, few of these maps make any comments on the limitations or generalizations made with their maps either. In this respect, the maps do not seek to give false impressions, but also do not make viewers aware of possible misinterpretation due to the information they are not able to show or the decisions made as to what to include and not include. Viewers of language maps can learn almost as much from reading between the lines of language maps as they can from what the maps set out to show them directly. The issues of language map construction are evident through the hints of the decisions made during map composition and the limitations of language datasets. For example, if a map shows "major" languages, what does "major" mean? How many "minor" languages are there?

Some mapmakers avoid the issue of creating symbology for more than one item per place and yet still show this quality. We noticed in our sample that in many maps the close proximity of features seemed to imply even more items per place than the symbology indicated. Crisscrossing labels, multiple labels within a polygon ("unanchored" labels to be discussed below), or the coalescence of point observations could be interpreted as implying more languages or language features per place than the symbology indicates due to the close proximity of features and the lack of definition as to where one ends and the other begins. By using the symbology of monolingual mapping, yet placing features or labels close together, some maps give the idea (or at least don't discount the idea) that some language features could bleed into one another in some areas. This strategy keeps mapmakers from bearing the responsibility of escalating complexity in their map symbology while also relying on map viewers to look closely at the spatial distribution of items and question what that might indicate. Although this is a rather noncommittal way of indicating possible language variable plurality in one place, it might be a suitable strategy since language information is in a constant state of change. None of the language mapping literature discusses this specific tactic, but it is a strategy that is open to visual interpretation and may or may not always be intended.

Summarizing the map symbology types using Ambrose and Williams' (1991) typology reinforced our other symbology findings. With polygons being the most common dimension used, it was no surprise that type I (chorochromatic map using areal units) was observed most frequently of all the symbology types. The frequency of type A, with its new interpretation, also makes sense. Language maps can quickly become complicated with hierarchies of symbology and language items so numerous that the map legends become cumbersome. For this reason, it is often easier to put the labels of specific data items directly on the map while only using general symbology definitions in the legend. This keeps the map legend simple and ties the specific language information directly to its spatial location without any symbology translation required in between. Three of the four quantified symbology types (types C, D, and G for point, point, and line symbology respectively) were the fewest used symbology types overall (each seen in less than 1% of the map sample). Quantified area symbols (type J) were observed in approximately 9% of maps. Either quantified point and line symbols are unpopular or quantitative data are rarely collected at scales applicable to or suitable for point and line symbology. It must also be noted that symbology type B combines "dot map" with a quantitative point symbol type (proportional circles), yet the symbology type is not listed under "quantified point symbols" (Figure 1). This somewhat confusing categorization of point symbol types might mask the use rate of quantified point symbols. Symbology type B was observed in over 16% of the map sample but the typology doesn't account for the breakdown between dot-map and proportional circle use. The number of symbology types used to classify each map reveals either the efficiency of the typology itself or the relative complexity of the maps in the sample, depending on your perspective. The fact that 57% of the map sample fell neatly into just one symbology category suggests either that Ambrose and Williams' typology is adept at succinctly describing over half of the map sample with a singular symbology category or that over half of the map sample has a rather simple, uncomplicated symbology scheme that relies on only one layer of symbology for its language component. With the very simple symbology typology, however, a map can easily fall into a singular category while possessing many unique and detailed components that are not captured by the scale of the typology. From this viewpoint, a single symbology type for a map indicates neither category efficiency of the typology scheme nor simplicity of map symbology design, but rather the basic nature of the typology used.

With no guidelines in place, design creativity has room to roam and the various unique symbology strategies observed in our language map sample are examples of this. The most difficult aspects of language mapping--linguistic plurality and data uncertainty--were also the areas where symbology creativity occurred. Experimentation is a plausible direction to take if traditional methods do not adequately capture the data or intended map message, so it is no surprise that language mapping's challenging features were also the ones used to explore new symbology territory. Some strategies, such as the use of "mixed" areas or map caveat statements, are simple in design yet very effective. Other strategies, like polygon fills designed to overlap, require careful planning and understanding of the data and its distribution. Still other strategies involve a degree of humility and honesty about the limitations of the work, such as the use of question marks with boundaries or having an "unknown" category. While the use of such features is probably done with great hesitation in fear that they will lessen the map's authority to viewers, this open acknowledgement of data uncertainty should be encouraged. The indication that the map creators are aware of data limitations and acknowledge the importance of conveying the information gaps to map users can actually make maps feel more reliable.

Some mapping solutions are creative, complicated, and effective like the zipper-like boundary shown in Figure 6 (Cohen 1973). This solid-line boundary is actually a great example of showing varying language transition zones, or "linguatones" (Luebbering 2011). It goes beyond merely showing a "mixed zone". It shows two languages intermingled with each other to different extents along the boundary, a characteristic that again requires considerable familiarity with the dataset and actual language environment. This language boundary area and variation in language intermingling are all achieved through creative use of a solid-line boundary.

The final unique strategy occurred with such frequency that we eventually reviewed our entire map sample for its use: unanchored (or floating) labels. While this use of labels not tied down to a point or line, or hemmed in by a single enclosed polygon, occurred in 17% of the map sample, we did not find any discussion of it in previous language-mapping literature. Just as the newly interpreted type A allows for map legends to be less complicated, the additional label aspect of "floating" unanchored on the map allows for language data to show uncertainty and fluidity without discussing these qualities or sorting out how to show them through conventional symbology. The font size, spacing, and orientation of the labels are altered to imply hierarchies of language use or importance without specifically stating anything on the matter. When more than one label occurs within a polygon or labels crisscross, language coalescence is again implied without having to be otherwise explained or symbolized. The frequency of this previously unaccounted for strategy outpaced eight of the Ambrose and Williams' symbol types in our map sample. Overall, the oddities in language map construction reveal that there is room for new symbology ideas and possibilities; language mapmakers have already set an example for challenging the status quo.

Updating Ambrose and Williams' typology

As alluded to throughout this discussion, observations from our map sample have indicated areas where Ambrose and Williams' (1991) typology falls short. The combination of dot-map and proportional circles into one map type, the absence of the often-used unanchored labels, or even the out-dated type M "computer-generated map", all hint to the need for a more updated typology. Ambrose and Williams did not attempt to capture every language mapping strategy. In their own words, "such is the variety of mapping techniques, in fact, that it is difficult to generalize about them at all" (Ambrose and Williams 1991, 301); their goal was simply to "reinforce this impression of variety" (Ambrose and Williams 1991, 301). With the published figure almost 20 years old, an updated typology is needed not because of any major failings in their work, but simply because it is time. Figure 8 is the result of the observations made in our map survey.

We suggest an updated language map symbology typology (Figure 8) configured similarly to that of Ambrose and Williams with a number of amendments that bring it up-to-date while also capturing elements observed in our survey that were previously unaddressed. Symbology types are still indicated by letters that can be used in combination to indicate the different symbology strategies combined within a map. Overall, the typology has been extended from types A through M (Figure 1) to types A through O (Figure 8). There are only two more symbology types in total, yet the new typology is a more inclusive symbology summary featuring most of the repeated features observed in our survey.

The changes made from the old to the new typology are discussed in the order that they appear in Figures 1 and 8. First, the updated typology features the new interpretation of type A, "employing the written word", which has been expanded from the original that referred to vocabulary terms placed on the map, to any language-related information found on the map through labels alone and not conveyed in the map legend or other symbology. This is the only update between typologies that was already implemented in the original use of Ambrose and Williams' typology categorization of the map sample. Type B of the new typology introduces the unanchored or floating labels repeatedly observed in our map sample. This new type is strictly the result of our study observations; we were unaware of this feature's use and frequency before our survey.

Qualitative and quantitative point symbols have been more clearly separated in the new typology with new symbol type additions to both. Dot-maps and proportional circle symbology were previously grouped as one type (Type B in Figure 1) but are now separated out (Types C and E respectively in Figure 8). Dot maps are separate from the qualitative and quantitative point symbol types as it was in Ambrose and Williams' typology because it represents two possible map variations one we observed and one we did not. The dot-map type observed in our survey refers to simple points representing the location of, for example, a speaker observation or language location. We did not observe any quantitative dot-density maps, where a dot represents a certain quantity of feature occurrences within an enumeration unit (Robinson et al. 1995). In dot density maps, each point does not represent a precise location, rather it represents a set quantity of the variable that occurs within the unit area. Although we did not observe any dot density maps in the sample, they are a good possible language visualization to use for conveying the relative density of language features (Wikle 1997). As a result, we have left the symbology category of "dot maps" vague so as to include this possible mapping type that may have been (but did not appear in our sample) or will be used at some point. The new typology features a new type (type D) of qualitative point symbols, the use of a set of symbols on one map that differ in a qualitative aspect such as shape or color (but not a color ramp). Qualitative point symbols are often seen on maps in linguistic atlases that need various ways to symbolize pronunciation differences. The quantitative point symbol section in Figure 8 includes: bar graphs and pie chart symbols as before; the proportional circles symbology that is now separated from dot-maps; as well as a new type, type H, of choroplethic or count point symbols. These point symbols feature a color ramp or numeric value indicating either an ordered degree of a quality (e.g. status of a threatened language ranging from potentially endangered to extinct) or a count (e.g. the number of extinct languages). This feature, while only observed in a few maps, was difficult to categorize using the symbol types in Figure 1 and therefore led to the creation of this new type. Line symbols as a whole remain unchanged between typologies save for the shift in letters used to represent each type. Diffusion maps are kept in the new typology; they are a distinct language map type, although they were not included in this survey for reasons discussed in the methods section.

The polygon symbols section received an overhaul in the form of eliminating two types and renaming a third. Type K in Ambrose and Williams' typology is removed from the new version since its distinction isn't symbology-based, but rather map unit-based. The type was used to indicate maps that used color-shaded political unit polygons for symbolizing language. This aspect can be accounted for in the new typology by the addition of a superscript to any polygon-based map type notation. A superscript "P" added to, for example, a map type N (e.g. [N.sup.P]), would indicate that the polygon map units are politically based. Type L in Figure 1, choropleth shadings based on a grid, is renamed to "Raster" to represent all grid-based maps. Finally, the most obvious needed change is the removal of the outdated type M "computer-generated map" from the old typology. Any older SYMAP-type map products encountered can instead be considered in general as a raster, grid-based map.

Table 9 shows the map sample categorized by the new typology. Types M and A were the frontrunners in frequency of use, matching their counterpart types I and A in Ambrose and Williams' typology (Table 7). However, the third most common symbology type, type B (unanchored/floating labels), is a characteristic that was not captured by the old typology. When categorized by the updated typology, over 30% of the map sample included a symbology type (new types B, D, or H) that was not in the Ambrose and Williams' typology. In other words, a simple update to the typology, guided by observations made from our map sample, improved the symbology classification for more than 70 maps in our study sample. The new typology is not exhaustive as there are always exceptions. However, it does reflect most of the trends that can be observed on language maps and revitalizes the study of language map construction by providing a synopsis of language mapping symbology that includes present day practices.

Summary and conclusions

In the absence of guidelines and rules it becomes necessary to learn from actual practices. In our desire to renew the investigation of language map construction, we studied the symbology strategies of produced language maps since established language mapping principles are nonexistent. Our survey of language map characteristics supports the generalized typology of Ambrose and Williams (1991) but also reveals other previously unaddressed trends. We found many examples of the language mapping problems noted in the literature, such as the prevalence of solid boundary lines, monolingual mapping, and the use of political mapping units. The survey results provide evidence that these issues cited in the past, with the most relevant literature at least 10 to 20 years old, are still present-day problems. However, we also observed different attempts to handle these problems, to represent issues of language data complexity and uncertainty through the use of, for example, unanchored labels, map caveats, nonsolid boundary lines, and overlapping symbology layers. These creative efforts to deal with language mapping issues indicate that language mapping is not a stagnant cartographic field; there is room for experimentation with visualization. This is even more so the case given the technology now available to us, especially with geographic information systems (GIS). The benefits of GIS, specifically its ease of data organization and the efficient flexibility of visualization, are important assets not available to the language map compilers of the past. With these new tools at hand, we can review language mapping characteristics as documented in this research to explore and expand upon the cartographic depiction of language information.

Language will always be an important topic. Tracking the spatial distribution of language is important for observing, understanding, and appreciating our cultural climate. Despite their flaws, language maps have consistently been used as textbook figures for lessons on cultural and linguistic diversity and will remain to serve this function. This survey is an effort to support and improve upon the educational value of language maps. The survey provides a summary of what has been done and what has been done the most often. It reveals which tactics are usual and which ones are rare. It is the starting point for pursuing possible avenues for improvement and finally fills a void by providing a baseline quantitative account of language mapping practices, a summary of language mapping methods generated from language maps themselves. The updated language map symbology typology is a work in progress, created as a tool intended to be questioned, challenged, and changed as language mapping progresses. Future research implementing concepts of uncertainty and its representation, exploring the use of raster surfaces for language data, and collecting volunteered geographic information (VGI) to increase participation and sample sizes are all potential avenues for language mapping research that can move the discipline forward (Luebbering 2011).


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Candice R. Luebbering (a) *, Korine N. Kolivras (b) and Stephen P. Prisley (c)

(a) Department of Geography, Virginia Tech, 115 Major Williams Hall, Blacksburg, VA 24061, USA; (b) Department of Geography, Virginia Tech, 123 Major Williams Hall, Blacksburg, VA 24061, USA; (c) Department of Forest Resources and Environmental Conservation, Virginia Tech, 319 Cheatham Hall, Blacksburg, VA 24061, USA

(Received 2 August 2011; accepted 23 April 2013)

* Corresponding author. Email:

Table 1. Frequency of coverage extents used in the map

Map coverage extent           # of maps    of map sample

World                                 29           12.08
Continent(s)                          34           14.17
Region (extends beyond one            36           15.00
Country                               91           37.92
Region within a country               35           14.58
US state                               3            1.25
City or community                     12            5.00
Total                                240          100.00

Table 2. Use of points, lines, and polygons for language data

Symbol dimension used    # of maps    % of maps

Points                           61        25.42
Lines                            46        19.17
Polygons                        162        67.50

Note: Percentages sum up to greater than 100% since some maps used
more than one symbol dimension.

Table 3. Generalized language variable types and frequency of use
within the map sample.

Generalized language
map variables                               Includes

Counts or proportions     Counts or proportions of speakers, counts,
                            or proportions of languages
Ethnolinguistic or
  linguistic groups
Language features         Accents, creoles, dialects, dialect
                            divisions, linguistic features, pidgins,
                            pronunciation, vocabulary, word usage
Language importance       Dominant languages, English status or use,
  or use                    leading languages, major languages, minor
                            languages, mother tongue, official
Language relationships    Language branches, language families,
  or categorization         language groups, language homeland,
                            language origin, language phyla, language
                            stock, language subfamilies, language
                            subgroups, language subphylum
Language status (ex.      Documented languages, language hotspots,
  extinct, threatened)      number of threatened languages, phases of
                            language decline, threatened status of
Other                     Bilingualism rate/bilingualism divide;
                            measurements: language diversity,
                            versatility, diversity index, frequency
                            scores, functional importance; speech
                            area; temporal extent of speaking area

Generalized language      # of    % of
map variables             maps    maps

Counts or proportions        26   10.83
Ethnolinguistic or           11    4.58
  linguistic groups
Languages                    89   37.08
Language features            78   32.50
Language importance          20    8.33
  or use
Language relationships       64   26.67
  or categorization
Language status (ex.          9    3.75
  extinct, threatened)
Other                        13    5.42

Table 4. Use of solid versus nonsolid boundary lines for language
items on maps.

Used solid boundary             % of     % of maps with
lines for language     # of      map      language item
items?                 maps    sample    boundary lines

Yes                     112     46.7          57.1
No                      84      35.0          42.9
N/A                     47      19.6

Note: Percentages do not sum up to 100%; three maps were double
counted as "Yes" and "No" because some language features on the map
used line symbology while others did not.

Table 5. Most common map unit categories and use of political
map units observed in the sample.

Map unit category                 # of maps    % of map sample

Language area (polygon)               77            32.08
Language family area (polygon)        38            15.83
Observation location (point)          25            10.42
Language location (point)             23             9.58
Isoglosses (line)                     18             7.50
Dialect area (polygon)                17             7.08
Country (polygon)                     14             5.83
Political map unit                    43            17.80
Nonpolitical map unit                198            82.20

Note: Many maps use more than one unit type for language data and are
therefore counted for each unit type used.

Table 6. Number of language items and language items per
place observed in the map sample.

Number of different
languages or
language features on     # of    % of map
the map                  maps     sample

1                         43       17.9
>1                        197      82.1

Number of language       # of    % of map    % of applicable
items per place          maps     sample           maps

1                         117      48.8            59.4
>1                        80       33.3            40.6

Table 7. Use of Ambrose and Williams' symbology types and
the top symbology types overall (combinations included). Refer
to Figure 1 for the definition of each symbology type.

Type    # of maps    % of maps    Top types    # of maps    % of maps

A           89         37.08          1            49         20.42
B           51         21.25          AI           41         17.08
C            1          0.42          B            25         10.42
D            2          0.83          A            23          9.58
E           33         13.75         Sum          138         57.50
F            8          3.33
G            1          0.42
1          112         46.67
1           22          9.17
K           32         13.33
L            4          1.67

Table 8. Sample of map caveat quotes observed.

Location of languages is approximate.

Boundary representation is not necessarily authoritative. (CIA 1997)

The boundaries on this map are somewhat artificial and pockets of
speakers of other languages will be found in areas where one language
is dominant. (Comrie, Matthews, and Polinsky 2003, 141)

By suggesting that the area assigned to a language or language family
uses that language exclusively, the map pattern conceals important
linguistic detail. Many countries and regions have local languages
spoken in territories too small to be recorded at this scale. (Getis,
Getis, and Fellmann 2008, Figure 7.19, 236-237)

This map indicates only the general location of larger groupings of
people, which may include smaller groups such as clans, dialects, or
individual languages in a group. Boundaries are not intended to be
exact. (Horton 2009)

Well over 100 languages are spoken in the region, the majority of them
by very small ethnic groups, and hence unrecordable on any save
the most detailed maps. (Milner-Gulland and Dejevsky 1998, 26)

Although the country can be divided into four main linguistic regions
as shown, people living in individual communities, especially in
the mountains, may use a language other than the prevailing local
one. (Rubenstein 2008, 171)

Table 9. Use of new typology symbology types and the top
symbology types overall (combinations included). Refer to
Figure 8 for the definition of each symbology type.

Type    # of maps   % of maps   Top types   # of maps   % of maps

A          89        37.08          M          58         24.17
B          39        16.25         AM          27         11.25
C          15         6.25          N          21          8.75
D          32        13.33        ABM          15          6.25
E           3         1.25          A          13          5.42
F           1         0.42          D          13          5.42
G           2         0.83
H           4         1.67
I          33        13.75
J           8         3.33
K           1         0.42
M         128        53.33
N          22         9.17
O           4         1.67

Figure 2. Distribution of source types for the map sample.

Atlas                    17%
Book                     24%
Government publication    9%
Journal article          13%
Map product               4%
Newspaper                 1%
Organization              3%
Textbook                  4%
Website                  25%

Note: Table made from pie chart.
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Author:Luebbering, Candice R.; Kolivras, Korine N.; Prisley, Stephen P.
Publication:Cartography and Geographic Information Science
Article Type:Report
Date:Nov 1, 2013
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