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I think the author is just a little bit behind the times in terms of organizing large corpuses of inter-related data. Tagging as a general idea is too fast-and-
by throwaway984393 5y ago
I think the author is just a little bit behind the times in terms of organizing large corpuses of inter-related data. Tagging as a general idea is too fast-and-loose without a system/structure to organize the tags. Semantic Web stacks are one way to improve on this using taxonomies and ontologies, query languages and data specs; they almost mention it in the alternative systems ("touples") but don't dig into just how hard it is to manage data using unstructured references (or even structured ones!).
Simple hierarchies are ..... simple. Tags are simple too, but they quickly devolve into new complexities as people try to figure out how to apply them, find them, organize them. Hierarchies aren't typically as difficult to manage because it boxes you into re-creating the same mental model for organization, just with different classifiers for each level of the hierarchy. They're less flexible, but they're easier to grok, maintain, and use.
My major concern is that there isn't really a need to "fix" hierarchies, it's just a nagging problem that someone doesn't want to deal with, so their solution is to make something more complicated.... and more complicated might not make it better. It should also be feasible to design applications to organize the files without having to rewrite filesystems.
- pimlottc 5y agoYou seem to know a lot about this; what is considered the "correct" way to organize data like this these days?
- throwaway984393 5y agoI couldn't claim to know what is "correct" and what isn't! I've just worked on projects to organize large collections of interrelated datasets (for example, to update correlations between concepts, to make search engines more effective, to identify related or dependent item relationships, etc) and for our project we used a Semantic Web stack. Browsing GitHub for "knowledge graph" or "knowledge management" seems to pop up some cool looking projects, but I think everyone is still trying to figure out what works for a particular use case rather than generally. I hope a real data scientist can reply with whatever the latest and greatest solutions are. Semantic Web tech for knowledge graphs are continuing to evolve, but also kind of old, and they're still mostly used for research projects. Part of that is probably because the terminology is unusual, and implementation leads you down a long rabbit hole of new and confusing concepts. So that's why I'm thinking that just sticking to a boring inefficient hierarchy might not be so bad...