Show HN: An extension to track your Wikipedia adventures(chromewebstore.google.com) Wiki Journey tracks your daily Wikipedia rabbit holes in a tree format. Available on Firefox and Chrome: https://addons.mozilla.org/en-US/firefox/addon/wiki-journey/ https://chromewebstore.google.com/detail/wiki-journey/lehenb... It's open source, feel free to contribute! https://github.com/demegire/wiki-journey |
Basically, I was reading way too much Wikipedia and not actually storing much information, so I have the extension shame me if I don't remember what I read.
It shapes who we are.
And sometimes knowledge of the existence of a topic is valuable.
[1] https://observablehq.com/@nitaku/tangled-tree-visualization-...
> A tree with multiple inheritance (sometimes called tangled tree) cannot be represented by using a classic tree visualization. It is technically a directed acyclic graph (DAG) with one (or more) nodes identified as root.
What is the difference between a DAG and a tangled tree? Isn't any DAG a tangled tree? I don't see immediately why a new definition is required.
An example might be: I have to include new AWS resources in a deployment, so I look up information about them, find examples and read about potential problems, security information, etc etc. That then becomes edits in a terraform file somewhere, with a Jita ticket, my own knowledge database (Emacs org-roam files in my case, Obsidian etc for other people). Then the feature branch gets a PR to dev, we might discuss changes in Teams (ugh) or a meeting. All of that seems ripe to be linked together conceptually, but the computer has no way to do that.
It makes me wonder if that could be fed into the right machine learning thing to at least start tracking this sort of work stuff. Heck just synchronizing my Firefox bookmarks (ff lets you tag your bookmarks) with my org-roam instance's tags would be useful. Tagged files in my knowledge base could be automatically linked to similarly tagged bookmarks.
I do find it ironic though that wikipedia is one of the major sites with the least amount of user tracking, and then users decide to implement the tracking themselves.
The concept reminds of https://browser.horse/ a bit, which has the concept of "trails" that track any links you visit. Great for research projects.
This reminds me of a python scraper I wrote a while back when I was learning to program - Youtube rabbithole: https://github.com/BlairCurrey/youtube-rabbithole
It basically just follows the next recommended video, recording the path along the way. More about tracing the youtube algorithm than tracking your own journey.
It seems likely that the extension could be customized to any Mediawiki instance? As an admin I'd love to be able to use it elsewhere. This looks like it could be a great tool working with test users on stuff like information architecture, to see the path of how they found information. (I know there are better tools for that, but something that focuses tightly on wiki interactions would be useful to me.)
A few years ago I did a university project where we looked into (internet) research and how information discovery and gathering could be improved. (https://www.kaimagnus.de/projects/halo)
There we had the concept of a similar looking tree. Users could then come back to their exploration and take notes, prioritize and sort.
It was only a concept back then, so it’s nice to see it in action.
Though I do still think it would be cool to have a toggleable overlay or something that shows the cyclic connections!
It's like a book titled "A History of [Object]" that traces what solved problems before the object, issues with old solutions, the emotional, financial, etc state of the inventor, why they chose this solution over that one, how the object was adopted and improved afterwards, other inventions spawned off the object, etc. Capturing the history of the object requires capturing the context around the object too
If it's not...then there's really nothing "left" on the table — if ever turns out to be valuable, you'll probably come across it again, when needed.
I constantly get a similar feeling. I'm speeding around from task to task, just grasping enough to get the current task done so I can get to the next one and the next one...
And somehow this is value-creating? Apparently it is, but it seems almost accidental, at that rate.
I'd rather slow down and appreciate the value as it moves through me, into whatever I'm doing.
I usually get more from the process, at the same time.
Reminds me of a floating point number. The bigger or smaller they get, the less accurate they become.
If you're chunking on a ton of data and tasks, you're getting less out of it. At a certain point, none of it even seems to enter your brain at all.
I really love the idea of digital knowledge bases, but as you said, I think we're leaving a lot on the table. I need to get back to my project of a user-owned-data knowledge base.
Seeing relevant bookmarks when I'm viewing a specific note in my database could be useful though. And finding pull requests related to a subject might also be useful.
So the idea would be to reduce the number of searches performed by the human. Automate and enhance rather than dump and forget.
I also remember not being explicitly taught that.
It sort of seems like trying to find enlightenment by chopping wood and carrying water at a monastery.
If critical thinking is something that spontaneously emerges in a learning environment, maybe we shouldn’t sell it as a benefit. “Some students experience deep insight into the nature of the mind. Results not typical.”
By the author's definition, multiple inheritance prohibits cycles. DAGs can be modeled as tree with back edges to non-ancestors. So I'm pretty sure tangled tree = DAG.
> For this example, someone could navigate away from one page, but potentially be linked back to it later down the adventure.
Good point, maybe "tangled tree with back edges to ancestors" is the really correct model for what the author wants. The key point of the visualization is to highlight the deviation from a standard DAG or tree.
> It is technically a directed acyclic graph (DAG)
But DAG's don't have 'roots', they just have nodes. The concept of roots makes it a tangled tree.