Show HN: Every great read I've come across, compiled into a knowledge graph(prashantbarahi.com.np) |
Show HN: Every great read I've come across, compiled into a knowledge graph(prashantbarahi.com.np) |
As something I will ever reference, it's basically useless. Which, I feel bad saying, because that suggests that I'm somehow considered in any way in this graph. But, the reason I mention it is because this and the rest of the "here's all my xyz knowledge/notes laid out for you to peruse" graphs and digital gardens are just bad ways of engaging with someone else's ideas.
The idea is there: start anywhere! Follow the meandering path! But, the experience is more: "well, I guess I need to start at the beginning again" (digital gardens) and "I guess I'll just pick a random node cuz they're all supposed to be equally interesting?" (the OP)
That having said. Thanks author for taking the time and trying.
(now my mind is just wandering, but some way to "aggregate" knowledge bases... maybe kind of like RSS but with full-text search and more hierarchical, with tags and multiple layers of navigation... that would be cool!)
Or am I just over-thinking that "s"?
Either way, this looks great. Randomly clicking a few entries finds stuff I wish I had found years earlier. Thanks a ton for sharing! I'll have to poke around more :)
This one is to the point. So, the collection was exported from my Pocket account. Whenever I find any interesting blogs, I save it there (with tags so that I can find them easily). The oldest entry dates back to 2017 and over time, I have accumulated about 700-ish articles.
Here's the backstory: https://twitter.com/nottherealpac/status/1545803998854205441
Hope this clarifies :)
Anyway, thanks again! This looks like a lot of good stuff, it's clearly years of effort and I'm very glad you shared.
language
"That author is always a good read."
https://www.merriam-webster.com/dictionary/read
> read (noun)
> something (such as a book) that is read
How is it useful?
On the one hand, manually tagged data is the first phase of making data useful in many knowledge systems. On the other hand, algorithmically scraping resources and creating a graph from that data is going to be bananas complicated.
Here's what I'm curious about. Can your curated graph be used to pick out same clusters from a superset of links which include the second graph?
Sure, what I'm describing is a search problem. And it's about words whether they're in a string, vector, or graph structure. And that's all very interesting in it's own right. What's also interesting is a fuzzy search that's fuzzy in a graphy way. Is that a thing? I don't know, but I want to know.
I tried the search, and found none of the following terms:
markup, annotation, micrometer, logarithm, memex, forth, lisp, thread, lathe, precision
I see "good blogs" and there's no hint as to why they are good, etc.
I like the preview of the individual articles, it would be good if something similar happened when clicking on a tag node. For my taste that would be just a straightforward list of articles tagged in that way but I can imagine there might be other ways.
I had not thought of publicly documenting samples of algorithms I have used in the past. I have an internal library of one-liners and bash scripts but I should publish these
> I have an internal library of one-liners and bash scripts but I should publish these
That's a great idea. Bash scripts are sort-of like regex to me (I have to recall them whenever I need them and then I forget them later) and bash scripts samples can really be useful. Looking forward to your Show HN.
Quick question: How did organizing data in this format help you?
So, here is a D3.js network graph that represents all of the wonderful reads I've ever found on the internet. The larger nodes are the tags, while the smaller ones are the links to the article.
So for example, using turtle syntax [1], instead of
<https://engineering.zalando.com/posts/2022/04/functional-tes...> <http://example.com/graph-edge> <https://www.testcontainers.org/>
have
<https://engineering.zalando.com/posts/2022/04/functional-tes...> <http://purl.org/dc/terms/subject> <https://www.testcontainers.org/>
The semantics of http://purl.org/dc/terms/subject is given at the url itself, but in brief:
> A topic of the resource.
> Recommended practice is to refer to the subject with a URI. If this is not possible or feasible, a literal value that identifies the subject may be provided. Both should preferably refer to a subject in a controlled vocabulary.
This would be similar to how wikidata expresses knowledge [2]:
<http://www.wikidata.org/entity/Q28315661> <http://www.wikidata.org/prop/direct/P921> <http://www.wikidata.org/entity/Q750997>
Or in English:
"Go To Statement Considered Harmful"(Q28315661)'s "main subject"(P921) is "goto"(Q750997)
This also makes it easier to query [4], for example, you could get all articles covering a "goto" with the following SPARQL[5] query:
SELECT ?item WHERE { ?item <http://www.wikidata.org/prop/direct/P921> <http://www.wikidata.org/entity/Q750997> }
May help to read the RDF primer [3] also.
[1]: https://www.w3.org/TR/turtle/
[2]: https://www.wikidata.org/wiki/Q28315661
[3]: https://www.w3.org/TR/rdf11-primer/
[4]: https://w.wiki/5RW2