This data looks nicely formatted already, so it would be easy to convert it to the more general CLDF formats that are used in all CLLD databases now. This would not change the data, but only add one more layer of comparability. In fact, it would require to add:
- an
etc folder that stores concepts and languages in TSV files
- a lexibank_dagswadesh.py script that runs the conversion
- as setup.py file that installs the data as a Python package
- a
cldf directory that stores the resulting data
- some additonal files that also help with the citation on Zenodo.
If you ever plan to launch your data in a CLLD website (potentially also via CLLD, where one could inquire, if time and space is there), CLDF would be the key, and we are by now experimenting with refined data representations, including alignments, and the like.
If you want, I could provide the relevant code in a PR. We have also online tutorials. Alternatively, I would prepare a CLDF package independently in our lexibank repository (which would also illustrate how conversion is done).
This data looks nicely formatted already, so it would be easy to convert it to the more general CLDF formats that are used in all CLLD databases now. This would not change the data, but only add one more layer of comparability. In fact, it would require to add:
etcfolder that stores concepts and languages in TSV filescldfdirectory that stores the resulting dataIf you ever plan to launch your data in a CLLD website (potentially also via CLLD, where one could inquire, if time and space is there), CLDF would be the key, and we are by now experimenting with refined data representations, including alignments, and the like.
If you want, I could provide the relevant code in a PR. We have also online tutorials. Alternatively, I would prepare a CLDF package independently in our lexibank repository (which would also illustrate how conversion is done).