Horizon 2020(H2020)818854Descriptive and Comparative Linguistic

Arias, L.

Becker, L.

Gijn, E. van

Norder, S.J.

Skirgård, H.

Witzlack-Makarevich, A.

Leiden University Scholary Publications

Glottospace: R package for language mapping and geospatial analysisof linguistic and cultural dataNorder, S.J.; Becker, L.; Skirgård, H.; Arias, L.; Witzlack-Makarevich, A.; Gijn, E. vanCitationNorder, S. J., Becker, L., Skirgård, H., Arias, L., Witzlack-Makarevich, A., & Gijn, E. van.(2022). Glottospace: R package for language mapping and geospatial analysis of linguisticand cultural data. Journal Of Open Source Software, 7(77). doi:10.21105/joss.04303 Version: Publisher's VersionLicense: Creative Commons CC BY 4.0 licenseDownloaded from: https://hdl.handle.net/1887/3513184 Note: To cite this publication please use the final published version (if applicable).glottospace: R package for language mapping andgeospatial analysis of linguistic and cultural dataSietze Norder 1,2, Laura Becker 3, Hedvig Skirgård 4, LeonardoArias 2,5, Alena Witzlack-Makarevich 6, and Rik van Gijn 21 Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands 2Leiden University Centre for Linguistics, Leiden University, Leiden, The Netherlands 3 Department ofGeneral Linguistics, University of Freiburg, Freiburg im Breisgau, Germany 4 Department of Linguisticand Cultural Evolution, Max-Planck-Institute for Evolutionary Anthropology, Leipzig, Germany 5Department of Evolutionary Genetics, Max-Planck-Institute for Evolutionary Anthropology, Leipzig,Germany 6 Hebrew University of Jerusalem, Jerusalem, IsraelDOI: 10.21105/joss.04303Software• Review• Repository• ArchiveEditor: Andrew StewartReviewers:• @fauxneticien• @skalyan91Submitted: 30 March 2022Published: 12 September 2022LicenseAuthors of papers retain copyrightand release the work under aCreative Commons Attribution 4.0International License (CC BY 4.0).SummaryThe glottospace R package facilitates the geospatial analysis of linguistic and cultural data.The aim of the package is to provide a streamlined workflow for geolinguistic analysis, includingdata entry, data import, cleaning, exploration, language mapping and visualisation, and export.Glottospace is also intended as an R interface to global linguistic and cultural databases suchas Glottolog, WALS, and D-PLACE, contributing to improved reproducibility of data analysis.Statement of needSeveral databases exist that capture aspects of linguistic and cultural diversity globally. However,there is a lack of interfaces to access and manipulate these databases, specifically within theR environment (R Core Team, 2022). For example, it is not straightfoward to link thesedatabases with data collected by researchers at smaller scales or particular sets of languages.While linguistic R packages have been developed for specific purposes (e.g., lingtypR (Becker,2022), qlcData (Cysouw, 2018), lingtypology (Moroz, 2017), and glottoTrees (Round, 2021)),there is currently no easy-to-use package that automates the most common tasks related toanalysing, visualising, and mapping (geo)linguistic data. glottospace aims to fill this gap byoffering a set of functions that, in essence, provide four things:1. Simplified access to global linguistic and cultural databases2. Standardized data structures for data collection, import, cleaning, and checking3. Functionalities to merge data from various linguistic and cultural datasets4. Streamlined workflows for geolinguistic data analysis and visualisationWe will now describe each of these elements in more detail.Existing global databases of linguistic and cultural diversity, such as Glottolog (Hammarströmet al., 2021), WALS (Dryer & Haspelmath, 2013), and D-PLACE (Kirby et al., 2016), arestructured according to the cross-linguistic data format (Forkel et al., 2018), allowing forthe integration of different databases. One way in which languages can be matched acrossdatabases is by using glottocodes, i.e., unique identifiers of languages, dialects and languagefamilies (Forkel & Hammarström, 2021). These glottocodes often have geospatial coordinatesassociated with them, allowing for geospatial analysis and visualisation. With glottospace,users can easily access the most recent version of these databases. Researchers can querythose databases, use them as a benchmark, or supplement their own data with additionalinformation (like geospatial coordinates, language family).Norder et al. (2022). glottospace: R package for language mapping and geospatial analysis of linguistic and cultural data. Journal of Open SourceSoftware, 7(77), 4303. https://doi.org/10.21105/joss.04303.1The glottospace package can generate empty data structures to facilitate data entry, or convertexisting databases (for example stored in an Excel or CSV file) into two standardized datastructures (Figure 1):• glottodata: a single data table (and optionally, metadata tables)– one row for each glottocode– any number of columns with linguistic/cultural features• glottosubdata: multiple data tables (and optionally, metadata tables)– one table for each glottocode∗ one row for each glottosubcode∗ any number of columns with linguistic/cultural featuresFigure 1: Examples of glottodata (left) and glottosubdata (right) without metadata tables.The glottodata structure is appropriate when one wants to assign one or more features to eachlanguage in the dataset (as, e.g., in WALS). The glottosubdata structure allows for assigningmore complex structures (inventories) to each language in the dataset, which may vary in sizefrom one language to another, such as phoneme inventories (Phoible; (Moran & McCloy, 2019)construction/morphological inventories (AUTOTYP; (Bickel et al., 2022), and subordinationstrategies in SAILS (Gijn, 2016).Although all metadata tables that can be generated for glotto(sub)data are optional, someof these tables can greatly facilitate the automation and reproducibility of further analysis.Examples of metadata tables that can be generated by glottospace are:• structure table: specify the type, possible levels, weight, group, and subgroup for eachvariable• description table: provide a description, reference, and remark for each variable• references table: provide a reference and page number for each glottocode (or variable)• remarks table: provide additional remarks for each glottocode (or variable)• contributors table: add the names of people who contributed the data• sample: specify a subset of glottocodes that should be used in further analysis• readme: add information about the person responsible for the data, including contactdetails and how to cite the data.The glottodata and glottosubdata structures are optimized to be linked with the aforementionedglobal databases, and allow for streamlined workflows for the analysis and visualisation oflinguistic and cultural data. For example, with one line of code, glottospace users can map aset of languages as either points or polygons, and colour them by a particular feature. However,Norder et al. (2022). glottospace: R package for language mapping and geospatial analysis of linguistic and cultural data. Journal of Open SourceSoftware, 7(77), 4303. https://doi.org/10.21105/joss.04303.2language mapping and visualisation is just one aspect of the package’s functionality, the aimof glottospace is to streamline entire workflows, facilitating common tasks such as:• read user data from a local path• convert data into glottodata or glottosubdata structures• perform quality checks and data cleaning (e.g., missing values, inconsistencies, andundefined glottocodes)• analyse languages and cultures based on relevant features (e.g., lexicon, phonemes,gender roles, and subsistence strategies)• create different kinds of maps and visualisations for a set of languages• export visualisations, maps, and datasets to be used in publications (Figure 2)• improve reproducibility in data analysisFigure 2: Isolate languages in South America, with major rivers in the background. This visualisation isgenerated with glottospace using one line of code. Although other map projections are supported, thedefault projection is the equal-area Eckert IV projection (following (McNew et al., 2019)).To enable this functionality, glottospace builds on a combination of spatial and non-spatialNorder et al. (2022). glottospace: R package for language mapping and geospatial analysis of linguistic and cultural data. Journal of Open SourceSoftware, 7(77), 4303. https://doi.org/10.21105/joss.04303.3packages, including sf (Pebesma, 2018), tmap (Tennekes, 2018), rnaturalearth (South, 2017),ggplot2 (Wickham, 2016), vegan (Oksanen et al., 2020), and dplyr (Wickham et al., 2021).The package is currently used by researchers and students in the field of comparative andareal linguistics as well as language typology and cultural anthropology. Furthermore, we areplanning to use the package for classroom teaching.AcknowledgementsSietze Norder, Leonardo Arias, and Rik van Gijn were supported by the European ResearchCouncil under the EU H2020 and Research and Innovation program (SAPPHIRE grant 818854).The authors would like to thank Simon Greenhill, Robert Forkel and Harald Hammarströmfor brainstorming about linguistic data formats and the functionality of the package. Finally,the authors are very grateful to Nay San, Siva Kalyan, and Andrew Stewart for reviewing andediting.ReferencesBecker, L. (2022). lingtypR: Easy data manipulation for typologists. https://gitlab.com/laurabecker/lingtyprBickel, B., Nichols, J., Zakharko, T., Witzlack-Makarevich, Alena Hildebrandt, K., Reßler,M., Bierkandt, L., Zúñiga, F., & Lowe, J. B. (2022). The AUTOTYP database. https://doi.org/10.5281/zenodo.5931509Cysouw, M. (2018). qlcData: Processing data for quantitative language comparison (QLC).Dryer, M., & Haspelmath, M. (2013). Dryer, Matthew S. & Haspelmath, Martin (eds.) TheWorld Atlas of Language Structures Online. Leipzig: Max Planck Institute for EvolutionaryAnthropology.Forkel, R., & Hammarström, H. (2021). Glottocodes: Identifiers linking families, languagesand dialects to comprehensive reference information. Semantic Web, 1, 1–8. https://doi.org/10.3233/sw-212843Forkel, R., List, J. M., Greenhill, S. J., Rzymski, C., Bank, S., Cysouw, M., Hammarström,H., Haspelmath, M., Kaiping, G. A., & Gray, R. D. (2018). Cross-linguistic data formats,advancing data sharing and re-use in comparative linguistics. Scientific Data, 5, 1–10.https://doi.org/10.1038/sdata.2018.205Gijn, R. van. (2016). Construction-based subordination data (SUB). In Muysken, Pieter et al.(eds.) South American Indian Language Structures (SAILS) Online. Jena: Max PlanckInstitute for the Science of Human History. (Available at https://sails.clld.org).Hammarström, H., Forkel, R., Haspelmath, M., & Bank, S. (2021). Glottolog 4.5. Leipzig: MaxPlanck Institute for Evolutionary Anthropology. (Available online at https://glottolog.org).Kirby, K. R., Gray, R. D., Greenhill, S. J., Jordan, F. M., Gomes-Ng, S., Bibiko, H.-J., Blasi,D. E., Botero, C. A., Bowern, C., Ember, C. R., Leehr, D., Low, B. S., McCarter, J.,Divale, W., & Gavin, M. C. (2016). D-PLACE: A global database of cultural, linguisticand environmental diversity. PLoS ONE, 11(7), 1–14. https://doi.org/10.1371/journal.pone.0158391McNew, G., Derungs, C., & Moran, S. (2019). Towards faithfully visualizing global linguisticdiversity. LREC 2018 - 11th International Conference on Language Resources and Evaluation,805–809. ISBN: 9791095546009Moran, S., & McCloy, D. (2019). PHOIBLE 2.0. Jena: Max Planck Institute for the Scienceof Human History. https://phoible.orgNorder et al. (2022). glottospace: R package for language mapping and geospatial analysis of linguistic and cultural data. Journal of Open SourceSoftware, 7(77), 4303. https://doi.org/10.21105/joss.04303.4Moroz, G. (2017). Lingtypology: Easy mapping for linguistic typology. https://CRAN.R-project.org/package=lingtypologyOksanen, J., Blanchet, F. G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P. R.,O’Hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Szoecs, E., & Wagner, H.(2020). vegan: Community Ecology Package. https://cran.r-project.org/package=veganPebesma, E. (2018). Simple Features for R: Standardized Support for Spatial Vector Data.The R Journal, 10(1), 439–446. https://doi.org/10.32614/RJ-2018-009R Core Team. (2022). R: A language and environment for statistical computing. R Foundationfor Statistical Computing. https://doi.org/10.1007/978-3-540-74686-7Round, E. R. (2021). glottoTrees: Phylogenetic trees in linguistics. https://github.com/erichround/glottoTreesSouth, A. (2017). rnaturalearth: World Map Data from Natural Earth. R package version0.1.0. https://cran.r-project.org/package=rnaturalearthTennekes, M. (2018). tmap: Thematic Maps in R. Journal of Statistical Software, 84(6), 1–39.10.18637/jss.v084.i06Wickham, H. (2016). ggplot2: Elegant graphics for data analysis. Springer-Verlag New York.https://ggplot2.tidyverse.orgWickham, H., Romain, F., Henry, L., & Müller, K. (2021). dplyr: A grammar of datamanipulation. R package version 1.0.7.Norder et al. (2022). glottospace: R package for language mapping and geospatial analysis of linguistic and cultural data. Journal of Open SourceSoftware, 7(77), 4303. https://doi.org/10.21105/joss.04303.5

Glottospace: R package for language mapping and geospatial analysis of linguistic and cultural data

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Glottospace: R package for language mapping and geospatial analysis of linguistic and cultural data

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