Taxonomy Is Hard
11–20 of 83 posts
Re: Taxonomy Is Hard
#12Taxonomy is a demon which separates people into perfectionists and non-perfectionists just before dragging both the kinds to hell of exceptions, weird relations and impractical location. Perfectionists get stuck spending infinite amounts of time engineering the taxonomy, non-perfections face the quirks later. Tags are better but can turn out to be even harder (for similar reasons, amplified combinatorially). Labels a…
Re: Taxonomy Is Hard
#13> Well, since you ask, here's Hans Reiser's old stuff:
https://reiser4.wiki.kernel.org/index.php/Future_Vision
https://reiser4.wiki.kernel.org/index.php/V4
(and http://lwn.net/2001/1108/a/reiser4-transaction.php3 )
. And here's some emails etc. I wrote in response:
https://web.archive.org/web/20040728044342/http://www.st-and...
https://marc.info/?l=linux-kernel&m=111624697710426
https://www.mail-archive.com/reiserfs-list@namesys.com/msg09...
https://www.mail-archive.com/reiserfs-list@namesys.com/msg20...
https://www.mail-archive.com/reiserfs-list@namesys.com/msg20...
https://www.mail-archive.com/reiserfs-list@namesys.com/msg20...
https://www.mail-archive.com/reiserfs-list@namesys.com/msg20...
, plus some of the discussion threaded from those posts. (Sorry, my stuff needs rewriting and updating but I'm not in the position to do it at present. If there's anything you would like to ask about please do. https://news.ycombinator.com/item?id=9809041 and https://news.ycombinator.com/item?id=10548477 touch on things that are a bit further down the line, but related—in particular, to the handling of "internal metadata" and files with a compound internal structure.)
Re: Taxonomy Is Hard
#14Multidimensional latent spaces based on content and other characteristics of the object is the real solution here.
Re: Taxonomy Is Hard
#15Taxonomy is a demon which separates people into perfectionists and non-perfectionists just before dragging both the kinds to hell of exceptions, weird relations and impractical location. Perfectionists get stuck spending infinite amounts of time engineering the taxonomy, non-perfections face the quirks later. Tags are better but can turn out to be even harder (for similar reasons, amplified combinatorially). Labels a…
How are "labels" different from tags?
E.g. the "javascript" tag implies the "programming" tag. I can even speculate there probably is a trait (linguists may suggest) which applies to some programming languages as well as to some spoken languages. This way tagging arguably can become even harder than taxonomy.
While a label is just a label.
Re: Taxonomy Is Hard
#16Taxonomies are a crutch that simplify a complex problem - usually too much to be useful. Multidimensional latent spaces based on content and other characteristics of the object is the real solution here.
Re: Taxonomy Is Hard
#17All true. Taxonomy is indeed hard. But, does it actually matter? It seems what matters is not how files are stored/organized, but how one can find the files one is looking for. Taxonomy is mostly a search problem. Yet, although one is usually capable of remembering specific or unique details about a file, it's still incredibly hard to search for a file or its contents effectively. Dropbox, to pick just one example, d…
Re: Taxonomy Is Hard
#18Well, if symlinks seem inelegant, there are hard links as well, you know. Ultimate tag system: for each tag, make a directory with corresponding name, fill with hard links to appropriate files stored in one big directory of mud. Of course, it all have to fit into a single disk drive, and actually deleting a file is difficult but hey, that must be easily solvable, details are left as an exercise for the reader.
Re: Taxonomy Is Hard
#19Re: Taxonomy Is Hard
#20For research papers (in PDF), I have a half-baked python solution I wrote myself that cobbles together the cermine pdf parser/content extractor, the whoosh full text search engine, and an ncurses-based interface.
For personal images, I use the elodie CLI tool, but I'd like to move away from it as I don't like how it modifies files by embedding metadata in them. For research/computer vision data, I use custom tooling based on sidecar files and a pg database kept in sync with the sidecars . For audio samples, I just use a commercial solution, sononym, that uses an sqlite database.
For other miscellaneous use cases, I've also used TMSU. Pretty nice as a more general purpose solution, except for the inherent issues mentioned by the article.
So yeah, I agree it's a hard problem.