Nicole van der Hoeven published one of her videos on using Obsidian on the topic of the ExcaliBrain plugin. The plugin is made by Zsolt Viczián, the same creator as the Excalidraw plugin which brings easy visualisation to Obsidian. I use Excalidraw within Obsidian with some regularity (I’m mostly text oriented).

It’s not mentioned in the video, but the ExcaliBrain plugin is clearly inspired by The Brain software, both in terms of types of links between notes, and how it shows them (even the placement of the little circles where links attach). The name suggests so too, and the plugin author names The Brain as source of inspiration in the github reposository. I used The Brain as desktop interface from 1997 until 2004-ish, and this plugin seems to bring The Brain as a visualisation layer to my notes. That alone is enough to try it out.

The plugin can both infer relationships between notes, through existing links, much as the general graph view in Obsidian does, but does so in a more navigable style. This I hope allows it to be used as a visual navigation interface to notes, something the graph view does not meaningfully, as The Brain so usefully did for me for a number of years.

You can also set explicit relationships by adding named links to your notes, for which it uses the inline data fields (yourfieldname::) that the DataView plugin makes possible. I already use that plugin so that’s not an extra step for me.
I disagree with Nicole van der Hoeven on her suggestion to comment out explicit relationships so that the plugin will visualise them but the note won’t show the links, except in edit mode.
The notes should always show all links I explicitly set, that’s the whole point of links.
Machine inferred links are a different matter, which deserve a toggle as they are suggestions made to me.
Links are my own and real work in my notes.

Setting explicit links (parent, child, friends ExcaliBrain calls them) is similar to how I already create links. When I write a new note I aim to link other notes in the way Soren Bjornstadt describes in a video of his touring his Zettelkasten. I make three links, if possible, from a new note. One to a higher level of abstraction note, one to a lower level of abstraction but more concrete note, and one to a related note at the same level. This creates ‘chains’ of 4 notes with a content-based implied order.

For example: a note on the role of public transport might link to urban mobility and the liveability of car-free city centers as higher abstration concepts, to a note on urban rail systems or bus networks as a lower abstraction level, to the German 2022 summer reduced fare scheme as an example, and to another communal public service like urban public internet as a same level but different type of note.

I strongly dislike the parent-child-sibling(-friend) vocabulary Excalibrain introduces though, as it implies an order of creation. Parents exist first, children from parents. This means for the way I described creating links in notes that abstract concepts come first. This is not how it mostly works for me. Abstract notions are often created from, intuited from, less abstratct ones. The scaffolding created by less abstract notes and concrete examples is what leads to them. Overarching concepts and insights emerge from linking lower level items. Thankfully the terms you actually use to denote such connections between notes can be freely chosen in the plugin settings. That is a design choice by Zsolt Viczián I greatly appreciate.

Nicole van der Hoeven in her run-through of ExcaliBrain also talks about this implied hierarchy, and mentions a higher level type of use, which is adding more semantics to links using the renaming options in the plugin settings. For instance to express lines of argumentation, and how material reflects on eachother (e.g. Note A reinforces / contradicts Note B). This is the type of linking that Tinderbox allows you to do visually too, which I’ve used a lot. She hasn’t used it that way herself yet she says, but suggests it’s likely the most valuable use case. I think that rings true. It’s where linking becomes the work you have to do yourself again, as opposed to lazy or automatic linking between notes.

I very much want to experiment with the ExcaliBrain plugin.


A screenshot after activating ExcaliBrain of the vicinity of a single note

Al in maart had ik in Utrecht een leuk gesprek met Martijn Aslander en Lykle de Vries als onderdeel van hun podcast-serie Digitale Fitheid. Digitale Fitheid is een platform over, ja precies dat, de digitale fitheid voor de kenniswerker.

In het gesprek hadden we het over persoonlijk kennismanagement (pkm) en de lange historie daarvan, en de omgang met digitale gereedschappen en de macht om die tools zelf vorm te geven. Maar ook over mijn werk, verantwoord datagebruik, de Europese datastrategie, Obsidian meet-ups, en ethiek. Er kwam aan het begin zelfs met veel kabaal een AWACS voorbij.

Een gesprek van een uur dat zo voorbij was. Achteraf denk je dan, heb ik wel coherente dingen gezegd? Terugluisterend nu bij publicatie, valt dat mee.

Mijn gesprek in de Digitale Fitheid podcast staat nu online. Kijk vooral ook even naar de andere gesprekken, die zijn zeker de moeite waard.

Here are some impressions of my increased usage of Hypothes.is, a social annotation tool, in the past few days.
I follow Chris Aldrich his Hypothes.is RSS feed, and his usage has been both a good example and source of learning in the past months, as well as a nudge to experiment and adopt Hypothes.is myself.

What follows is a list of some early impressions that I formulated earlier today in an email. I thought I might as well post them here.

  • I played with the API to get a grip of how I might interact with the annotations I make, and with those of others I’m interested in. Added the existence of annotations to my blogposts in WordPress through the API too.
  • The Obsidian plugin to get annotations into my notes is an absolute prerequisite, because I need those notes in my own workflow.
  • I find working in browser for annotations somewhat distracting and uncomfortable (and I need to remind myself that they will end up in my notes, I feel the urge to also download it directly to my notes.)
  • I try to add an Archive link to the annotated article as the first link. It is slowly becoming habitual.
  • I mention existing notes in my annotations when I make them in Obsidian. Because it is one context that is a matter of starting a link [[ and I have forward search through all note titles. In hypothes.is being browser based this is a bit harder, as it means switching tools to retrieve the correct note titles. They do then work when they end up in Obsidian of course. At the same time, in my earlier use of a markdown downloader I would just mention those associations in the motivation to save a link, which is worse. Hypothes.is sits in the middle of saving a bookmark with motivation and annotating in Obsidian itself.
  • I do have some performative urges when annotating publicly. Maybe they will disappear over time.
  • The firefox hypothes.is bookmarklet I use doesn’t seem to play nice with archive.org. There’s another I haven’t tested yet.
  • I notice that any public annotations are licensed CC0 (public domain). Not sure what I think about that yet. It’s a logical step as such, but I don’t fully see yet what it may mean for subseqeunt learning processes internally and further down the process of creating insights or outputs. Is CC0 also applied to closed groups (educational settings e.g.)? Private annotations are just that, and don’t have CC0, but then you miss out on the social aspects of annotation.
  • My thoughts keep wandering to interacting with hypothes.is without using it directly to annotate webarticles through the browser. Are there any tools or people who build on or share with hypothes.is using the W3C standards / API, but don’t necessarily use hypothes.is themselves? Or run their own instance, which should be possible? I suspect that would open opportunities for a more liquid experience between this blog, my notes, and annotated articles.

Bookmarked Using GPT-3 to augment human intelligence: Learning through open-ended conversations with large language models by Henrik Olof Karlsson

Wow, this essay comes with a bunch of examples of using the GPT-3 language model in such fascinating ways. Have it stage a discussion between two famous innovators and duke it out over a fundamental question, run your ideas by an impersonation of Steve Jobs, use it to first explore a new domain to you (while being aware that GPT-3 will likely confabulate a bunch of nonsense). Just wow.
Some immediate points:

  • Karlsson talks about prompt engineering, to make the model spit out what you want more closely. Prompt design is an important feature in large scale listening, to tap into a rich interpreted stream of narrated experiences. I can do prompt design to get people to share their experiences, and it would be fascinating to try that experience out on GPT-3.
  • He mentions Matt Webbs 2020 post about prompting, quoting “it’s down to the human user to interview GPT-3“. This morning I’ve started reading Luhmann’s Communicating with Slip Boxes with a view to annotation. Luhmann talks about the need for his notes collection to be thematically open ended, and the factual status or not of information to be a result of the moment of communication. GPT-3 is trained with the internet, and it hallucinates. Now here we are communicating with it, interviewing it, to elicit new thoughts, ideas and perspectives, similar to what Luhmann evocatively describes as communication with his notes. That GPT-3 results can be totally bogus is much less relevant as it’s the interaction that leads to new notions within yourself, and you’re not after using GPT-3s output as fact or as a finished result.
  • Are all of us building notes collections, especially those mimicking Luhmann as if it was the originator of such systems of note taking, actually better off learning to prompt and interrogate GPT-3?
  • Karlsson writes about treating GPT-3 as an interface to the internet, which allows using GPT-3 as a research assistant. In a much more specific way than he describes this is what the tool Elicit I just mentioned here does based on GPT-3 too. You give Elicit your research question as a prompt and it will come up with relevant papers that may help answer it.

On first reading this is like opening a treasure trove, albeit a boobytrapped one. Need to go through this in much more detail and follow up on sources and associations.

Some people already do most of their learning by prompting GPT-3 to write custom-made essays about things they are trying to understand. I’ve talked to people who prompt GPT-3 to give them legal advice and diagnose their illnesses. I’ve talked to men who let their five-year-olds hang out with GPT-3, treating it as an eternally patient uncle, answering questions, while dad gets on with work.

Henrik Olof Karlsson

In reply to Call for Model Examples of Zettelkasten Output by Chris Aldrich

Even while on hiatus I obviously cannot ignore Chris Aldrich’s call for examples of output creation systems and the actual output created with Zettelkasten style note card systems. For two reasons. One is that I fully agree with him that having such examples publicly visible is important. The other is that I recognise his observations about the singular focus on system design and tweaking often being a timesink precluding outputs (with the loudest voices often being utterly silent on output).

Here’s a first list of outputs from my system, without the receipts though as I’m writing this away from home with limited tools. After the list I’ll make a few general observations as well.

  • I have created 2 or 3 slide decks for client internal and conference presentations from my conceptual notes. First searching for notes on the topic, and the contextual factors of where the slide deck will be used. Then gathering the findings in what I call an ’emergent outline’ (Ahrens calls them speculative outlines). Or perhaps I already have an overview of sorts in the form of an ‘elephant path’ (a map of content, or annotated topical index) which normally help me navigate.
  • I have written blogposts directly from my notes. This is now easier than before, since earlier this year I created a way of publishing to this site from my internal notes. This allows me to write in a note, linking internally or including, all within the notes environment and then push the result out to the website.
  • I created some new personal insights from new connections within my notes. Not sure if that counts towards Chris’ definition of outputs. This results in new notes where the edge, i.e. the newly found link between two notions, gets expressed as a note in its own right. The first such connection (between my notions of Maker Households and Networked Agency) happened when I was about 35 notes ‘in’.
  • For a recent panel at a conference I collated my talking points from my notes
  • I use my notes a lot in work conversations, pulling up concepts as needed. I used to do this to pull up facts and earlier meeting notes with the same participants. Now I also use this to provide richer input into the conversations themselves, including pointing to sources and references. This emerged during the many video calls in the pandemic lockdowns, where it was easy to pull up additional material on one of my screens. Now that I have more meetings in person again, I find I still do this automatically. Whatever material I mention I also link in my own meeting notes. This has been remarked upon by conversation partners as a valuable thing.
  • I have some elephant paths I regard as output in their own right. One currently important to me is the Practices elephant path. It gives an overview of things I want to approach as a practice (which I place somewhere on the spectrum between habit/routine on one end and literacy (in the Rheingoldian sense of skill plus community) on the other end. Practices are the sweet spot to me for (groups of) knowledge workers to implement fields of theory in their own daily work
  • I maintain a client website directly from my notes on EU digital and data legislation. I have conceptual notes for all the regulations involved and maintain summaries alongside them. Those summary notes are automatically synced to GitHub and then published on Github pages as well as the client’s own domain. These same summaries also serve as outline and text for my frequent presentations on this subject, where the slidedeck is kept up to date from the notes that I am certain are always up to date because they are the notes I work with daily.

Some other observations:

What constitutes output? The ‘Luhmann had 90k notes and wrote 70 books’ mantra makes for a rather daunting benchmark to be compared against. I propose we count outputs that have utility to its creator. For me then there are two types of outputs from my notes. A group that is the result of better project tracking, allowing me to pick up where I previously left of, which is a valuable ratcheting effect. Me building my own micropub tools resulted from such ratcheting in 15 minute increments. This group of outputs results from notes, but not the conceptual notes of my ‘Garden of the Forking Paths’ (ie my Zettelkasten style collection). The other group results from re-using and re-arranging the material in my ‘Garden of Forking Paths’ and the example outputs listed above follow from it. In a sense all my work is an output of my notes and my experience, and my tools have always been aiding in my work. Yet there is a qualitative difference.

I have used notes based PKM for over two decades, and in hindsight it was mostly focused on reporting conversations, project stuff, conversations with myself, and many many examples of things I thought relevant. Those I would tag extensively, and I think most of those historic tags would now be their own conceptual notes, expressing the communality of the tagged examples and material, or expressing the link/edge between two or three of the tagged source notes as a notion.

Many of my conceptual notes (now 1000+) and ideas plus non-conceptual atomic notes (another 500 or so) stem from ‘atomising’ my archive of blogposts, and my presentations of the last 10-15 years. Many notes are thus created from earlier outputs themselves.

I recognise what Stephen Downes remarked, that creating the notes is the valuable part towards pattern recognition, and making output needs further gathering of new material. In part this is because adding things to my notes is aiding memory. Once it’s noted it’s no longer novel, and in that sense looses part of the surprisal (informational worth) that led to its creation in the first place. If outputs in my own mind need to be novel, then my notes are limited in value. (This goes back to earlier conversations of the 90% is crap heuristic which I see as feeding impostor syndrom. Outputs imo highly connected to impostor syndrom.

I don’t think I have actual established processes for outputs yet, I’d like to, and I don’t yet feel outputs created suggest as-effective-as-can-be processes yet. Maybe that is because I have not been really tracking such outputs and how I created them. I have become better at starting anything with interrogating my notes first, and putting them together, before starting exploration further afield. Often I find I already have some useful things, which gives a headstart in exploring anything new: there’s something to connect new findings to.

I do not think my current notes could yield something along the lines of a book, other than the nonsense kind of a single idea padded out with anecdotes. I also feel the method of information collection isn’t good enough to base any work on academically. This goes back to the earlier remark as to what qualifies as output of good enough quality.

Bookmarked Web Annotation Data Model by World Wide Web Consortium (W3C)

I wasn’t aware of it, but there’s a W3C model for annotations (in JSON). It was mentioned in the book Annotation I’ve been reading in the past weeks. Not sure if this is something I have a use for, but it may be an interesting way to transform and share book notes on this site. It was suggested that Hypothes.is uses this model. There’s also a Hypothes.is API which suggests it might be possible to pull annotations from there, although I don’t suppose you could push them there as a way of publishing annotations.

The Web Annotation Data Model specification describes a structured model and format to enable annotations to be shared and reused across different hardware and software platforms. … The specification provides a specific JSON format for ease of creation and consumption of annotations based on the conceptual model …, and the vocabulary of terms that represents it. This specification was derived from the Open Annotation Community Group’s outcomes. … This document was published by the Web Annotation Working Group as a Recommendation

W3C