I wonder if it would be productive to have language archive discussions via stack exchange. OLAC implementation, cataloging, and indexing discussions.
https://area51.stackexchange.com/faq
1000 questions in 6 months with 70% answers... that means 6 people asking one question a day for 6 months. Do we have that many questions? Do we have that big of a community?
There are several views in the OLAC website. Each with specific purposes.
The following example points to the need for users to be able to sort collection by license, relationships, and extent.
I am looking for large spoken corpora of spontaneous speech in any
language (ideally > 100 hours) with a time-aligned transcription. I am
not committed to a specific genre as long as it is spontaneous speech.
It should be available as a download (for research, no commercial use),
ideally free but I may be able to pay for it as well.
There are several Dublin Core Uses... but what are the models behind them? Are they the same? Are they different? If they are different then does this mean that Dublin Core is more like a brand name than a metadata standard?
RSS: https://web.resource.org/rss/1.0/modules/dcterms/
HTML: https://www.dublincore.org/specifications/dublin-core/dcq-html/; https://www.dublincore.org/specifications/dublin-core/dc-html/
HTML: https://www.hjp.at/doc/rfc/rfc2731.html ; https://www.ietf.org/rfc/rfc2731.txt
Note that in https://www.ietf.org/rfc/rfc2731.txt they use DC1.0
When another application profile "borrows" the DC property/term/element... how do they borrow it? https://exiv2.org/tags-xmp-dwc.html
This seems promising for OLAC.
http://d-scholarship.pitt.edu/42973/
https://www.ncserialsconference.org/slides/2022/2022-1B.pdf
https://opencatalogingrules.org/
https://archive.org/details/podcast_electronic-serials-cataloging_386018207
https://wiki.rice.edu/confluence/display/METACAT/Cataloging+Continuing+Resources
https://www.tandfonline.com/doi/full/10.1080/01639374.2017.1388324
https://www.tandfonline.com/doi/abs/10.1080/1941126X.2018.1494014
https://wiki.rice.edu/confluence/display/METACAT/Cataloging+Continuing+Resources
https://web.library.yale.edu/book/export/html/570
https://github.com/WeblateOrg/language-data
https://alcts.libguides.com/alcts_standards/continuing_resources
https://www.tandfonline.com/doi/abs/10.1080/01639374.2017.1388324?journalCode=wccq20
https://alcts.libguides.com/alcts_standards/continuing_resources
https://www.loc.gov/aba/pcc/conser/word/Module0.docx
https://www.loc.gov/marc/bibliographic/bd008s.html
https://www.ala.org/alcts/confevents/upcoming/webinar/031815
https://archive.org/details/podcast_advanced-serials-cataloging-_386018196
https://archive.org/details/podcast_electronic-serials-cataloging_386018207
https://www.ala.org/alcts/mgrps/crs/
RDA & WEMI
http://www.mlalibrary.org/resources/Documents/Quickand%20DirtyRDA_MLA2016_TracyPizzi.pdf
Here are some links about German Grammar Books which are interesting for use in OLAC examples.
https://www.thoughtco.com/best-german-grammar-books-4150500
https://towardsdatascience.com/fuzzy-string-matching-in-python-68f240d910fe
https://www.activestate.com/blog/how-to-implement-fuzzy-matching-in-python/#:~:text=As%20mentioned%20above%2C%20fuzzy%20matching,strings%20are%20to%20one%20another.
What if my import pd data array was the OLAC metadata schema?
https://www.semanticscholar.org/paper/A-Gentle-Introduction-to-Topic-Modeling-Using-Saxton/38742c56eadfdf11fb7218f7702c8fccfc78bd95
https://gist.github.com/umbertogriffo/5041b9e4ec6c3478cef99b8653530032
https://towardsdatascience.com/contextualized-topic-modeling-with-python-eacl2021-eacf6dfa576
How to Use Bertopic for Topic Modeling and Content Analysis?
https://melaniewalsh.github.io/Intro-Cultural-Analytics/05-Text-Analysis/08-Topic-Modeling-Text-Files.html
https://asandeepc.bitbucket.io/courses/inls613_summer2019/lectures/08-lda_topic_modeling.pdf
http://derekgreene.com/slides/topic-modelling-with-scikitlearn.pdf
https://ourcodingclub.github.io/tutorials/topic-modelling-python/
https://stackabuse.com/python-for-nlp-topic-modeling/
https://www.toptal.com/python/topic-modeling-python
https://towardsdatascience.com/end-to-end-topic-modeling-in-python-latent-dirichlet-allocation-lda-35ce4ed6b3e0
While doing my Masters Thesis, I took a look at the contributor roles declared for various works. One thing I noticed is that even though Stuart McGill contributed two corpora to ELAR when these corpora get translated to OALC the translation mucks the metadata so that only one resource shows up with his name.
I asked the archive director about this and my understanding/recollection from that conversation is that metadata was piped through the TLA. https://lat1.lis.soas.ac.uk/ds/asv/?0&openpath=538104 I think the above record was also at the preveious link... but it doesn't resolve currently and there have been technology stack changes at ELAR since my Thesis was released. Here is the interface in the Internet Archive for a different record.
http://web.archive.org/web/20200616011131/https://lat1.lis.soas.ac.uk/ds/asv/;jsessionid=00127741134CA14440824DA736655134?0&openhandle=2196/00-0000-0000-0012-D580-4
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