issue_comments

Happy Birthday Datasette!

I am a librarian at the Université du Québec à Montréal (UQAM) and I've been using Datasette to publish excerpts of our library data. There are several use cases I'm working with as a proof of concept : 1. New titles list : based on reports of recent acquisitions by subject, discipline, etc. 2. List of all UQAM theses and dissertations : based on an extract of bibliographic records 3. List of all publications by UQAM Authors : based on an extract of bibliographic records

See our prototype under construction here : https://datasette-bib.uqam.ca/ (some bits and pieces have been translated into French)

Datasette is amazing, there is so much potential here for libraries. Thanks to Simon and all the contributors for this outstanding effort. Also sqlite-utils deserves special mention as incredibly handy and useful.

This probably counts as a case study: https://github.com/eyeseast/spatial-data-cooking-show. Even has video.

Seriously, though, this workflow has become integral to my work with reporters and editors across USA TODAY Network. Very often, I get sent a folder of data in mixed formats, with a vague ask of how we should communicate some part of it to users. Datasette and its constellation of tools makes it easy to get a quick look at that data, run exploratory queries, map it and ask questions to figure out what's important to show. And then I export a version of the data that's exactly what I need for display.

I use Datasette to analyze blocklists by using csv-to-sqlite to pull their contents into a database and Datasette to look around through them. I also use its REST API to query said database as part of filtering out garbage from domains found in those blocklists.

Nothing spectacular yet but I think this falls under "cool/cute application of datasette": improving fakedata performance for fun. tl;dr I used datasette to visualize benchmarking data.

Hi @simonw and thanks for the great tools you're publishing, your dedication is inspiring!

I work for the French Ministry of Culture on a surveying tool for objects protected for their historical value. It is part of a program building modern public services called beta.gouv.fr.

In that context I'm using data published by the Ministry that I have ingested into datasette and published on a free Fly instance : https://collectif-objets-datasette.fly.dev . I have also ingested another data set with infos about french cities on this instance so that I can perform joined queries.

The surveying tool synchronizes its data regularly from this datasette instance, and I also use it to perform queries when asked generic questions about the distribution of objects. (The data is not very accessible as it's undocumented and for internal usage mostly)

Tim Sherratt on Twitter: https://twitter.com/wragge/status/1591930345469153282

Where do I start? The #GLAMWorkbench now includes a number of examples where GLAM data is harvested, processed, and then made available for exploration via Datasette.

https://glam-workbench.net/

For example the GLAM Name Index Search brings together 10+ million entries from 240 indexes and provides an aggregated search using the Datasette search-all plugin:

https://glam-workbench.net/name-search/

Most recently I converted PDFs of the Tasmanian Postal Directories to a big Datasette instance: https://updates.timsherratt.org/2022/09/15/from-pdfs-to.html the process is documented and reusable.

I'm a cryptic crossword enthusiast and have spent a lot of time scraping and parsing cryptic crossword clues from various blogs, forums and publications. The result is over half a million clues from cryptic crosswords over the past twelve years, including the clue, answer, puzzle date, puzzle name and a link to the original source. This is all hosted using Datasette, which has been a delight to use: https://cryptics.georgeho.org/

This dataset is a significant work of crossword archivism and scholarship, as acquiring historical crosswords and structuring their contents require focused effort and tedious cleaning that few are willing to do for such trivial data - for example, according to this 2004 selection guide, the Library of Congress explicitly does not collect crossword puzzles. Anecdotally, I know that many constructors/setters of cryptic crosswords use this dataset as a resource, and some even simply call it "the database" - this is probably one of the most impactful data projects I've worked on!