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JeffreyBenjaminBrown
hode
Haskell2019–2022
JeffreyBenjaminBrown / hode

hode

rslt, take five-ish

4Distinct people
15Mentions
0Explicit recommenders
151GitHub stars
REPOSITORY AT A GLANCE

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What it is

rslt, take five-ish

GitHub

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:03:16 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year15 dated mentions

Observed mentions: 2019-04-06 13:29:47 UTC to 2022-07-30 04:23:22 UTC.

02462019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 6 mentions; 1 submissions, 5 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2022

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
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PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC615
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC303
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC413
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC202

What Hacker News says

15 sources
It's an interesting idea. Maybe I should try. I suspect, though, that I want control over every node, no matter how general. The thing about my notes is they contain only information I think I might need. I have, for instance, an "emotions" node. I'm sure the Wikidata node for emotions is interesting, but I want my own node too. I tried to square this circle once by writing Hode[1], which permits encoding certain data as relevant to me, and then filter my view accordingly when I wanted. But the encoding process (i.e. the user experience when adding data to one's knowledge base) was so hard that I gave up. [1] https://github.com/JeffreyBenjaminBrown/hode
In A tour to my Zettelkasten note clusters
One example of a data structure implementing faceted classification would be the multitree [0]. Unfortunately multitrees seem to receive far less support than 2 other data structures it intermediates: trees and DAGs. k-d trees [1] are close but use cases seem to predominantly target data with inherently ordinal (rather than nominal) dimensions. Further abstraction could lead to the knowledge graph [2] or graph databases. In all cases, the availability of "low-code" tools (in the domain of single-user personal information management, at least) seems sparse. I have been looking for some time, but the search continues. [0]: https://en.wikipedia.org/wiki/Multitree [1]: https://en.wikipedia.org/wiki/K-d_tree [2]: https://github.com/JeffreyBenjaminBrown/hode
In Designing better file organization around tags, not hierarchies (2017)
I believe the most important question regarding personal knowledge bases is how to make them social. In grad school I was for a year part of a small study group. We shared notes, on paper and aloud. It made each of us far, far better at the subject than we could have been on our own. And we were at most 7 people (sometimes only 3). When developing Hode[1], and when helping develop Semantic Synchrony[2], I imagined some kind of mind-meld utopia where superbeings would not just frolic in but also tend each others' knowledge gardens. (Brandon Toner on Twitter[3] even introduced me to a hashtag for them ... which I can't remember ...) Reading nonlinearly is a faster way to accumulate knowledge than reading linearly. That's is why people who really care prefer newspapers to watching the news on TV. And a format that lets lots of people contrib
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ute their input can potentially convey more than a format that locks you into reading a single author. Alas, the potential for noise is higher too -- but still, this is why Wikipedia has been so wildly successful. One might ask, "We've already got Wikipedia; what possible improvement on that do you see?" The thing about Wikipedia is it presents what the author(s) consider(s) settled knowledge. It is a place for record, not a place for debate. A good shared knowledge base would by contrast also resemble Twitter -- but more organized, more navigable. In practice the personal knowledge bases I've seen look much more like silos. I once frolicked for an afternoon through Andy Matuschak's[4], which was quite enjoyable. But it was mostly about ... can you guess? ... how to build a knowledge base. If someone finds a scheme that scales, I believe it could be much more powerful than what we currently call AI. [1] https://github.com/JeffreyBenjaminBrown/hode [2] https://github.com/synchrony/smsn/ [3] https://twitter.com/brandontoner [4] https://notes.andymatuschak.org/Knowledge_work_should_accret...
In Note Taking in 2021
The issue at the heart of both the Zettelkasten and the PARA methods seem to be that a person wants their notes to be connected in useful ways. To an extent, "ordinary" knowledge graphs permit this -- where by "ordinary" I mean that the edges are unlabeled. Things are related to other things, but you have to infer the relationship yourself after looking at both of its members. Graphs with labeled edges seem clearly better. But then what if you want a relationship with more than two members? (Or less! "Not" and "maybe" are two important unary relationships.) And what if you want a relationship's members to themselves be relationships? This is the nature, after all, of most information. Any but the simplest sentence is a relationship between relationships. "Children ask for cookies because cookies have sugar", for instance, is a "because" r
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elationship bewteen an "ask for" relationship and a "have" relationship. Once you've reified your relationships that way, you'd like to be able to search intelligently through them. "Ordinary" knowledge graphs let you see all of a thing's children, or parents, or maybe in some cases all it's descendents and ancestors up to some level of recursion. Better would be something that lets you ask targeted questions, like "Show me everything Sally has asked me to do that does not require a computer." To my knowledge there's only one program that lets you reify your data and query it in the ways I've described. It's called Hode, for Higher Order Data Editor. I wrote it. https://github.com/JeffreyBenjaminBrown/hode
In Remembering what you Read: Zettelkasten vs. P.A.R.A
I think the point most guides overlook consists of the internal semantics of using a Zettelkasten, Luhmann essentially used it to create a paragraph (Zettel) & subchapter (Zettel Sequence, but note they of course sometimes he'd not manage to fit an entire paragraph on one Zettel due to margin limitations) branching & branchable, recursively self-referential choose your own adventure hypertextbook, from which he'd then generate regular textbooks. Hence why he said that his books basically wrote themselves — to write a book, he'd 'just' enter the Zettelkasten, and copy out everything he'd already written there on the topic, picking between branches & branchings as he went back, forth & side-to-side within it. Hence why if one looks close, one can find Luhmann seemingly self-plagiarising paragraphs from books he'd previously written. I suspe
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ct a similar mechanic sits behind the (in this sense very ignorant) accusations of self-plagiarism against Slavoj Zizek. As such, one might wish to instead consider using Hypertext Fiction tools for creating a Zettelkasten, such these two (proprietary software, Mac OS X only, unfortunately): http://www.eastgate.com/Tinderbox/ http://www.eastgate.com/storyspace/ Note that there exists an EXTREMELY useful plugin for Tinderbox which implements Stretchtext: https://natematias.com/stretchtext/ Now gimme a combination of what roamresearch.com does with the above, but using the data structure of Hode: https://github.com/JeffreyBenjaminBrown/hode But with support for zzstructure like hyperthogonality: https://github.com/JeffreyBenjaminBrown/digraphs-with-text/i... And secretly use the patching patches feature of pijul.org in the background so version control actually becomes sanely doable, throw in elastic tab stop support, and maybe an entire kitchensink in which someone let a mixture of ChrysaLisp, SmallTalk, Hazel, Scala 3, /r/nosyntax, Inferno, RINA, GNUnet, & every single proof assistant and theorem prover sit for a tad bit long, and then MAYBE we can stop living in the dark ages of computing. (Yes I'm bitter) P.S.: Identity Transclusion ≠ Instance Transclusion P.P.S.: Birth & Death of Javascript, anyone?
In Luhmann's Zettelkasten
> (typically) the more something machine friendly the less it's human friendly. I believe I have solved some of that problem. Hode (the Higher Order Data Editor), a kind of generalization of graph databases, lets a user enter data in a manner which I believe is as similar as possible to natural language. To encode the fact "cats kill birds" as a "kill" relationship between "cats" and "birds", you just write "cats #kill birds". Relationships involving other relationships can be represented with similar ease, and relationships involving any number of elements. The query language is not much more complicated -- for instance, everything that kills birds would be "/e /it #kills birds". https://github.com/JeffreyBenjaminBrown/hode
In The sad state of personal data and infrastructure
Agreed. Human thinking is arbitrarily high-order -- we use statements about statements about statements with no particular natural complexity limit. This seems to me the big limitation of knowledge graphs: The majority of real-world information, just like the majority of natural-language sentences, are highly nested relationships among relationships. That was my motivation for writing Hode[1], the Higher-Order Data Editor. It lets you represent arbitrarily nested relationships, of any arity (number of members). It lets you cursor around data to view neighboring data, and it offers a query language that is, I believe, as close as possible to ordinary natural language. (Hode has no inference engine, and I don't call it an AI project -- but it seems relevant enough to warrant a plug.) [1] https://github.com/JeffreyBenjaminBrown/hode
In Cyc
Hode[1] (the Higher Order Data Editor), which is free, solves some of these problems. (I wrote it. It's still evolving but it works already.) > metadata is hard Hode lets you encode and search any kind of information -- entities, relationships bewteen entities, relationships between relationships, relationships of any arity (number of members). Hash, the language in which one adds and searches for data in Hode, is very close to natural language. I'll give examples below, based on the article's author's wishes. > Let me compare my reading list with another to see overlap This is the "and" operator. (There are also "or" and "difference" operators.) The query in Hash would look like /find (/eval /it #is-in (reading list #of mary)) & (/eval /it #is-in (reading list #of peter)) > Allow me to tag books instead of placing them into static l
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ists Hode lets you do even better than tags -- you can classify the meaning of the tag. For instance, here are two commands that would add two tags to a book: /add The Wisdom of Crowds #was a best-seller /add The Wisdom of Crowds #(helps understand) finance > Be tied to my highlights, annotations, and bookmarks in a non-proprietary, searchable, and shareable format Hode is free software, and the data format it uses is dirt-simple. Hode permits encoding and searching just about anything I can think of. Hode cannot yet create the data for you to search, though -- so far you've got to enter the data yourself. > Let me query this tool like a relational database. For example: show me all books about scaling startups recommended by people I follow on Twitter or by people they follow. /find (/eval /it #(is about) scaling startups) & (/eval (/eval I #follow /it #on Twitter) #recommends /it) > Help me deal with prioritization Hode lets you order your search results according to any transitive binary relationship -- "read before" or "is more important than" or "was written before", whatever you want. [1] https://github.com/JeffreyBenjaminBrown/hode
In Digital Tools I Wish Existed
Could be a tech solution to the reputation problem? Some kind of distributed social media- and wikipedia-like system where information is signed by its author(s), and where people are able to produce metadata rating the factuality of information and authors. Currently people can create such information, of course. But liars routinely deny well-documented things in their past, and those denials are effective to their intended audience. And currently someone can debunk a lie, but there's no systematic way to find everyone who testifies that it's untrue. And while finding all of a claim's supporters and debunkers would be a great first step, a truly good (i.e. skeptical) reader would want to be able to find their arguments, too. I'm skeptical that current AI could automate the job of indexing that information -- understanding controversial a
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rguments seems likely to require true intelligence. I happen to have made a system[1] in which indexing any kind of data or metadata is extremely easy, requiring little more than knowing some natural language. (Deciding what kind of information you want to encode is hard, but once you've decided that, encoding it is easy.) [1] https://github.com/JeffreyBenjaminBrown/hode
In The Information Apocalypse (2018)

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