Developing methods for reproducible research in linguistics: a first step
Date
2017-01-06
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Abstract
Reproducible research in other fields has developed various software tools that facilitate the publishing of code and results in a single document that are linked directly to the data. In mainstream linguistics, however, such software does not exist. The workflows for including linguistic examples in published work typically involve manual methods of copying and pasting text from a database into a word processing document. These manual methods are error-prone and time-consuming--often involving tedious tasks of aligning glosses in tables or with tabs. Furthermore, the examples in these documents are in no way linked to the corpus. This poster presents a first-attempt at developing a family of scripts called glossbox that link data, code, and analysis. At present, glossbox works with the typesetting software LaTeX, allowing users to semi-automatically import examples directly from the corpus. These examples require little to no manual manipulation and automatically produce citations to the corpus.
Description
Poster: Reproducible research in other fields has developed various software tools that facilitate the publishing of code and results in a single document that are linked directly to the data. In mainstream linguistics, however, such software does not exist. The workflows for including linguistic examples in published work typically involve manual methods of copying and pasting text from a database into a word processing document. These manual methods are error-prone and time-consuming--often involving tedious tasks of aligning glosses in tables or with tabs. Furthermore, the examples in these documents are in no way linked to the corpus. This poster presents a first-attempt at developing a family of scripts called glossbox that link data, code, and analysis. At present, glossbox works with the typesetting software LaTeX, allowing users to semi-automatically import examples directly from the corpus. These examples require little to no manual manipulation and automatically produce citations to the corpus.
Keywords
data citation, attribution, Linguistics
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1
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Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported
Attribution-NonCommercial-ShareAlike 3.0 United States
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