
@software{beastling14,
  title = {{{BEASTling}}},
  shorttitle = {A Linguistics-Focussed Command Line Tool for Generating {{BEAST XML}} Files.},
  author = {Maurits, Luke and Forkel, Robert and Kaiping, Gereon A.},
  year = {2019},
  month = jun,
  abstract = {A linguistics-focussed command line tool for generating BEAST XML files},
  copyright = {BSD-2-Clause},
  version={1.5.1},
  url={https://github.com/lmaurits/BEASTling/}
}

@inproceedings{cldfbench,
    title = "{CLDFB}ench: Give Your Cross-Linguistic Data a Lift",
    author = "Forkel, Robert  and
      List, Johann-Mattis",
    booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2020.lrec-1.864",
    pages = "6995--7002",
    abstract = "While the amount of cross-linguistic data is constantly increasing, most datasets produced today and in the past cannot be considered FAIR (findable, accessible, interoperable, and reproducible). To remedy this and to increase the comparability of cross-linguistic resources, it is not enough to set up standards and best practices for data to be collected in the future. We also need consistent workflows for the {``}retro-standardization{''} of data that has been published during the past decades and centuries. With the Cross-Linguistic Data Formats initiative, first standards for cross-linguistic data have been presented and successfully tested. So far, however, CLDF creation was hampered by the fact that it required a considerable degree of computational proficiency. With cldfbench, we introduce a framework for the retro-standardization of legacy data and the curation of new datasets that drastically simplifies the creation of CLDF by providing a consistent, reproducible workflow that rigorously supports version control and long term archiving of research data and code. The framework is distributed in form of a Python package along with usage information and examples for best practice. This study introduces the new framework and illustrates how it can be applied by showing how a resource containing structural and lexical data for Sinitic languages can be efficiently retro-standardized and analyzed.",
    language = "English",
}

@software{lingpy,
  author       = {Johann-Mattis List and
                  Robert Forkel},
  title        = {{LingPy}. A {Python} Library for Historical Linguistics},
  month        = jul,
  year         = 2021,
  publisher    = {Zenodo},
  version      = {v2.6.8},
  doi          = {10.5281/zenodo.5144474},
  url          = {https://doi.org/10.5281/zenodo.5144474}
}

@article{cldf-paper,
  title = {Cross-{{Linguistic Data Formats}}, Advancing Data Sharing and Re-Use in Comparative Linguistics},
  author = {Forkel, Robert and List, Johann-Mattis and Greenhill, Simon J. and Rzymski, Christoph and Bank, Sebastian and Cysouw, Michael and Hammarstr{\"o}m, Harald and Haspelmath, Martin and Kaiping, Gereon A. and Gray, Russell D.},
  year = {2018},
  month = oct,
  journal = {Scientific Data},
  volume = {5},
  pages = {180205},
  issn = {2052-4463},
  doi = {10.1038/sdata.2018.205},
  abstract = {The amount of available digital data for the languages of the world is constantly increasing. Unfortunately, most of the digital data are provided in a large variety of formats and therefore not amenable for comparison and re-use. The Cross-Linguistic Data Formats initiative proposes new standards for two basic types of data in historical and typological language comparison (word lists, structural datasets) and a framework to incorporate more data types (e.g. parallel texts, and dictionaries). The new specification for cross-linguistic data formats comes along with a software package for validation and manipulation, a basic ontology which links to more general frameworks, and usage examples of best practices.},
  copyright = {Creative Commons Attribution 4.0 International License (CC-BY)},
  langid = {english},
  keywords = {CALC,cross-linguistic data formats,reproducibility,standardization,TAP-Paper,tap-phylo},
}

@misc{cldf11,
  title = {{{CLDF}} 1.1.2},
  shorttitle = {Cldf/Cldf},
  author = {Forkel, Robert and Cysouw, Michael and List, Johann-Mattis and Rzymski, Christoph and Greenhill, Simon J. and Moran, Steven},
  year = {2021},
  month = may,
  doi = {10.5281/zenodo.4804030},
  abstract = {CLDF: Cross-Linguistic Data Formats},
  howpublished = {Zenodo},
}

@article{kaiping2019subgrouping,
  title = {Subgrouping the {{Timor}}-{{Alor}}-{{Pantar}} Languages Using Systematic {{Bayesian}} Inference},
  author = {Kaiping, Gereon A. and Klamer, Marian},
  year = {2019},
  month = apr,
  doi = {10.31235/osf.io/9s5hj},
  abstract = {This paper refines the subgroupings of the Timor-Alor-Pantar (TAP) family of Papuan languages, using a systematic Bayesian phylogenetics study. While recent work indicates that the TAP family comprises a Timor (T) branch and an Alor Pantar (AP) branch (Holton et al. 2012, Schapper et al. 2017) the internal structure of the AP branch has proven to be a challenging issue, and earlier studies leave large gaps in our understanding. Our Bayesian inference study is based on an extensive set of TAP lexical data from the online LexiRumah database (Kaiping \& Klamer, 2019). Systematically testing different approaches to cognate coding, loan exclusion, and explicit modelling choices, we arrive at a subgrouping structure of the TAP family that is based on features of the phylogenies shared across the different analyses. Our TAP tree differs from all earlier proposals by inferring the East-Alor subgroup as an early split-off from all other AP languages, instead of the most deeply embedded subgroup inside that branch.},
  copyright = {Creative Commons Attribution 4.0 International License (CC-BY)},
  keywords = {TAP-Paper},
}

@article{kaiping2021burst,
  title = {Burst {{Clock}}},
  author = {Kaiping, Gereon A. and Neureiter, Nico},
  year = {(under review)},
  journal = {Journal of Language Evolution}
}

@article{lexirumah-paper,
  title = {{{LexiRumah}}: An Online Lexical Database of the {{Lesser Sunda Islands}}},
  shorttitle = {{{LexiRumah}}},
  author = {Kaiping, Gereon A. and Klamer, Marian},
  year = {2018},
  month = oct,
  journal = {PLOS ONE},
  volume = {13},
  number = {10},
  pages = {e0205250},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0205250},
  abstract = {The Lesser Sunda Islands in eastern Indonesia cover a longitudinal distance of some 600 kilometres. They are the westernmost place where languages of the Austronesian family come into contact with a family of Papuan languages and constitute an area of high linguistic diversity. Despite its diversity, the Lesser Sundas are little studied and for most of the region, written historical records, as well as archaeological and ethnographic data are lacking. In such circumstances the study of relationships between languages through their lexicon is a unique tool for making inferences about human (pre-)history and tracing population movements. However, the lack of a collective body of lexical data has severely limited our understanding of the history of the languages and peoples in the Lesser Sundas. The LexiRumah database fills this gap by assembling lexicons of Lesser Sunda languages from published and unpublished sources, and making those lexicons available online in a consistent format. This database makes it possible for researchers to explore the linguistic data collated from different primary sources, to formulate hypotheses on how the languages of the two families might be internally related and to compare competing hypotheses about subgroupings and language contact in the region. In this article, we present observations from aggregating lexical data from sources of different type and quality, including fieldwork, and generalize our lessons learned towards practical guidelines for creating a consistent database of comparable lexical items, derived from the design and development of LexiRumah. Databases like this are instrumental in developing theories of language evolution and change in understudied regions where small-scale, pre-industrial, pre-literate societies are the majority. It is therefore vital to follow reliable design choices when creating such databases, as described in this paper.},
  copyright = {Creative Commons Attribution 4.0 International License (CC-BY)},
  langid = {english},
  keywords = {historical linguistics,Islands,Languages,Lexedata,Lexicon,Linguistic morphology,Metadata,Semantics,TAP-Paper,tap-phylo,Vocabulary},
}

@inproceedings{list2012lexstat,
  title = {{{LexStat}}: Automatic Detection of Cognates in Multilingual Wordlists},
  shorttitle = {{{LexStat}}},
  booktitle = {Proceedings of the {{EACL}} 2012 {{Joint Workshop}} of {{LINGVIS}} \& {{UNCLH}}},
  author = {List, Johann-Mattis},
  year = {2012},
  series = {{{EACL}} 2012},
  pages = {117--125},
  publisher = {{Association for Computational Linguistics}},
  address = {{Stroudsburg, PA, USA}},
  keywords = {Lexedata,TAP-Paper,tap-phylo},
  url = {https://aclanthology.org/W12-0216}
}

@article{list2017potential,
  title = {The Potential of Automatic Word Comparison for Historical Linguistics},
  author = {List, Johann-Mattis and Greenhill, Simon J. and Gray, Russell D.},
  year = {2017},
  month = jan,
  journal = {PLOS ONE},
  volume = {12},
  number = {1},
  pages = {e0170046},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0170046},
  abstract = {The amount of data from languages spoken all over the world is rapidly increasing. Traditional manual methods in historical linguistics need to face the challenges brought by this influx of data. Automatic approaches to word comparison could provide invaluable help to pre-analyze data which can be later enhanced by experts. In this way, computational approaches can take care of the repetitive and schematic tasks leaving experts to concentrate on answering interesting questions. Here we test the potential of automatic methods to detect etymologically related words (cognates) in cross-linguistic data. Using a newly compiled database of expert cognate judgments across five different language families, we compare how well different automatic approaches distinguish related from unrelated words. Our results show that automatic methods can identify cognates with a very high degree of accuracy, reaching 89\% for the best-performing method Infomap. We identify the specific strengths and weaknesses of these different methods and point to major challenges for future approaches. Current automatic approaches for cognate detection\textemdash although not perfect\textemdash could become an important component of future research in historical linguistics.},
  keywords = {Algorithms,Clustering algorithms,Evolutionary biology,historical linguistics,Language families,languages,Multiple alignment calculation,Phonology,TAP-Paper,tap-phylo},
}

@article{maurits2017beastling,
  title = {{{BEASTling}}: A Software Tool for Linguistic Phylogenetics Using {{BEAST}} 2},
  shorttitle = {{{BEASTling}}},
  author = {Maurits, Luke and Forkel, Robert and Kaiping, Gereon A. and Atkinson, Quentin D.},
  year = {2017},
  month = aug,
  journal = {PLOS ONE},
  volume = {12},
  number = {8},
  pages = {e0180908},
  issn = {1932-6203},
  doi = {10.1371/journal.pone.0180908},
  abstract = {We present a new open source software tool called BEASTling, designed to simplify the preparation of Bayesian phylogenetic analyses of linguistic data using the BEAST 2 platform. BEASTling transforms comparatively short and human-readable configuration files into the XML files used by BEAST to specify analyses. By taking advantage of Creative Commons-licensed data from the Glottolog language catalog, BEASTling allows the user to conveniently filter datasets using names for recognised language families, to impose monophyly constraints so that inferred language trees are backward compatible with Glottolog classifications, or to assign geographic location data to languages for phylogeographic analyses. Support for the emerging cross-linguistic linked data format (CLDF) permits easy incorporation of data published in cross-linguistic linked databases into analyses. BEASTling is intended to make the power of Bayesian analysis more accessible to historical linguists without strong programming backgrounds, in the hopes of encouraging communication and collaboration between those developing computational models of language evolution (who are typically not linguists) and relevant domain experts.},
  copyright = {All rights reserved},
  keywords = {Evolutionary linguistics,language,Language,Language families,Phylogenetic analysis,phylogenetics,Syntax,TAP-Paper,tap-phylo},
}

@techreport{pollock2015metadata,
  type = {Recommendation},
  title = {Metadata Vocabulary for Tabular Data},
  author = {Pollock, Rufus and Tennison, Jeni and Kellogg, Gregg and Herman, Ivan},
  year = {2015},
  month = dec,
  number = {REC-tabular-metadata-20151217},
  institution = {{W3C}},
  abstract = {Validation, conversion, display, and search of tabular data on the web requires additional metadata that describes how the data should be interpreted. This document defines a vocabulary for metadata that annotates tabular data. This can be used to provide metadata at various levels, from groups of tables and how they relate to each other down to individual cells within a table. The metadata defined in this specification is used to provide annotations on an annotated table or group of tables, as defined in [tabular-data-model]. Annotated tables form the basis for all further processing, such as validating, converting, or displaying the tables.},
  langid = {english},
  url = {https://www.w3.org/TR/2015/REC-tabular-metadata-20151217/}
}


@article{gunnink2022bantu,
  author={Gunnink, Hilde and Chousou-Polydouri, Natalia and Bostoen, Koen},
  year = {accepted},
  title={Divergence and contact in {S}outhern {B}antu language and population history: a new phylogeny in cross-disciplinary perspective},
  journal = {Language Dynamics and Change}
  }



@article{grollemund2015bantu,
  ids = {grollemund2015bantua},
  title = {Bantu expansion shows that habitat alters the route and pace of human dispersals},
  author = {Grollemund, Rebecca and Branford, Simon and Bostoen, Koen and Meade, Andrew and Venditti, Chris and Pagel, Mark},
  year = {2015},
  month = oct,
  journal = {Proceedings of the National Academy of Sciences},
  volume = {112},
  number = {43},
  pages = {13296--13301},
  issn = {1091-6490},
  doi = {10.1073/pnas.1503793112},
  abstract = {Unlike most other biological species, humans can use cultural innovations to occupy a range of environments, raising the intriguing question of whether human migrations move relatively independently of habitat or show preferences for familiar ones. The Bantu expansion that swept out of West Central Africa beginning {$\sim$}5,000 y ago is one of the most influential cultural events of its kind, eventually spreading over a vast geographical area a new way of life in which farming played an increasingly important role. We use a new dated phylogeny of {$\sim$}400 Bantu languages to show that migrating Bantu-speaking populations did not expand from their ancestral homeland in a ``random walk'' but, rather, followed emerging savannah corridors, with rainforest habitats repeatedly imposing temporal barriers to movement. When populations did move from savannah into rainforest, rates of migration were slowed, delaying the occupation of the rainforest by on average 300 y, compared with similar migratory movements exclusively within savannah or within rainforest by established rainforest populations. Despite unmatched abilities to produce innovations culturally, unfamiliar habitats significantly alter the route and pace of human dispersals.},
  langid = {english},
  pmid = {26371302},
  keywords = {Bantu,Bayesian phylogenetic inference,family: Bantu,human dispersal,languages,output,phylogenetics,phylogeography,Phylogeography},
}

@inproceedings{edictor,
    address = {Valencia},
    author = {List, Johann-Mattis},
    booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics. System Demonstrations},
    keywords = {JavaScript, annotation, etymology, _calc},
    pages = {9-12},
    publisher = {Association for Computational Linguistics},
    title = {A web-based interactive tool for creating, inspecting, editing, and publishing etymological datasets},
    url = {http://edictor.digling.org},
    year = {2017}
}


@article{gray2009language,
  ids = {gray2009languagea},
  title = {Language phylogenies reveal expansion pulses and pauses in {{Pacific}} settlement},
  author = {Gray, Russell D. and Drummond, Alexei J. and Greenhill, Simon J.},
  year = {2009},
  month = jan,
  journal = {Science},
  volume = {323},
  number = {5913},
  pages = {479--483},
  issn = {1095-9203},
  doi = {10.1126/science.1166858},
  abstract = {Debates about human prehistory often center on the role that population expansions play in shaping biological and cultural diversity. Hypotheses on the origin of the Austronesian settlers of the Pacific are divided between a recent ``pulse-pause'' expansion from Taiwan and an older ``slow-boat'' diffusion from Wallacea. We used lexical data and Bayesian phylogenetic methods to construct a phylogeny of 400 languages. In agreement with the pulse-pause scenario, the language trees place the Austronesian origin in Taiwan approximately 5230 years ago and reveal a series of settlement pauses and expansion pulses linked to technological and social innovations. These results are robust to assumptions about the rooting and calibration of the trees and demonstrate the combined power of linguistic scholarship, database technologies, and computational phylogenetic methods for resolving questions about human prehistory. Geographical distribution of Austronesian languages reveals the rate and direction of migrations from Taiwan 5200 years ago. Geographical distribution of Austronesian languages reveals the rate and direction of migrations from Taiwan 5200 years ago.},
  copyright = {American Association for the Advancement of Science},
  langid = {english},
  pmid = {19164742},
  keywords = {Bayesian phylogenetic inference,main,phylogenetics,TAP-Paper,tap-phylo},
}

@article{list2021lexibank,
  title = {Lexibank: {{A}} public repository of standardized wordlists with computed phonological and lexical features},
  shorttitle = {Lexibank},
  author = {List, Johann-Mattis and Forkel, Robert and Greenhill, Simon J. and Rzymski, Christoph and Englisch, Johannes and Gray, Russell D.},
  year = {2021},
  month = sep,
  doi = {10.21203/rs.3.rs-870835/v1},
  langid = {english},
  keywords = {computational linguistics,cross-linguistic data formats,cross-linguistic resource,historical linguistics,lexical data},
}
