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Daniel van der Merwe
Daniel van der Merwe

Posted on • Originally published at danielvandermerwe.com

Visual Representations Of Interconnectedness and Depth

I was introduced to the concept of using patterns to convey information density in this digital garden note by Azlen. Similarly, Maggie Appleton also uses iconography to visually differentiate between seedling, budding and evergreen notes in her digital garden. They inspired me to create my own pattern system to convey the interconnectedness and depth of notes on my website.

In order to create a pattern system for categorizing notes I had to define some factors that differentiate notes from each other. I selected the following criteria to try and capture connectedness and depth of each note:

  • Incoming links (Backlinks): These represent how many other notes refer or link back to a particular note. A higher number of backlinks indicates that the note is a crucial reference or cornerstone in the digital garden.
  • Outgoing links: This measures how many other notes a particular note refers to. It can indicate the breadth of a note and its interconnectedness within the digital garden.
  • Word count: A note's length can often signify its depth or thoroughness on a subject. Longer notes might delve deeper into a topic, while shorter ones could be more concise or introductory.
  • External links: These demonstrate how a note connects to external resources or references outside the digital garden. It's a nod to the fact that no note exists in isolation and that our knowledge often builds on external sources.

Criteria and Weights

I then needed to figure out a way to score notes based on these criteria. After a lot of coffee and tinkering I settled on the following approach.

I decided on some arbitrary weightings for each criterion based on absolutely no research at all, I just went with my gut and some rudimentary reasoning. I'll tweak these weightings as the site grows.

I'll use code snippets to explain the approach I took.

const incomingLinkModifier = 3;
const outgoingLinkModifier = 1.5;
const externalResourceModifier = 2;
const wordCountModifier = 0.005;
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I then work out a score for each criterion:

const incomingLinkScore = incomingLinkCount * incomingLinkModifier;
const outgoingLinkScore = outgoingLinkCount * outgoingLinkModifier;
const externalLinkScore =
  externalResourceModifier * Math.log(1 + externalResourceCount);
const wordCountScore = wordCount * wordCountModifier;
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Pretty self explanatory, but it's worth noting the reason I used logarithmic scoring on the external link is because of posts like [[loadout-update-q3-2023|Loadout Update (2023/Q3)]] . This post has many external links which in normal cases wouldn't be a problem, but in this case it created an abnormal inflation of the score the post was given. So I used logarithmic scoring to apply some diminishing returns on the use of external links.

In the future I might consider adding different weighting options for different post types but for now this will do.

Introducing the Nexus Score

To calculate a score for each note based on the the weighting calculations presented some challenges. Just because a note has many outgoing links does not mean it is equal to a note that has many words.

My first approach was to tally up the scores but it didn't convey any meaningful information based on connectedness to other notes for example. Just by looking at a score you can't know if it has that score because of many incoming links or because it has a lot of words.

So the approach I settled on was to apply a multi-dimensional scoring approach.

const linkDominanceThreshold = 10;
const linkDominanceScore = incomingLinkScore - outgoingLinkScore;

let dominanceState;

if (Math.abs(linkDominanceScore) < linkDominanceThreshold) {
  dominanceState = "H"; // Hub Note
} else if (linkDominanceScore > 0) {
  dominanceState = "R"; // Receiver Note
} else {
  dominanceState = "T"; // Transmitter Note
}
const totalScore =
  Math.abs(linkDominanceScore) + wordCountScore + externalLinkScore;
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Ok, so what's going on here?

Firstly I calculate a dominance score by subtracting incoming link count from outgoing link count. This will either give me a negative or positive number. If the absolute (regardless of sign) dominance score is less than 10 it's a "Hub" note. It means there is a balance of incoming and outgoing links to and from the note. If it has a positive score it is a "Receiver" note that has many incoming notes. If it has negative score it is a Transmitter note with many outgoing links to other notes.

The final part of the equation is to then add the absolute link dominance score, word count score and external link score together for a final total score.

I'm then left with two outputs that form what I'm calling Nexus Score.

  • A letter representing link dominance: H|R|T
  • A number representing a total score of all the other scores

Visually Representing Nexus Scores

To visually represent these scores on notes I had to figure out ranges for the numbers. Once again I went with gut feel based on the current scores.

const iconScoreRanges: IconScoreRanges = {
  R_Fragment: [0, 10],
  R_Basic: [10, 26],
  R_Developed: [26, 42],
  R_Advanced: [42, 68],
  R_Integrated: [68, Infinity],

  H_Fragment: [0, 10],
  H_Basic: [10, 26],
  H_Developed: [26, 42],
  H_Advanced: [42, 68],
  H_Integrated: [68, Infinity],

  T_Fragment: [0, 10],
  T_Basic: [10, 26],
  T_Developed: [26, 42],
  T_Advanced: [42, 68],
  T_Integrated: [68, Infinity],
};
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These ranges will definitely be adjusted over time as the site grows.

The link dominance score and total score can now be used to match a score range. As an example a note with more outgoing links than incoming links and a total score of 25 will resolve to T_Basic.

Here is a full map of the Nexus Score icons.

Image description

Icons source: https://tabler-icons.io/

Future Considerations

  • Normalization of scores (not straight forward to do efficiently)
  • Different weightings and score ranges based on note types (theme post, loadout update, note, fragment, etc.)
  • Add a citation library and adjust the nexus score to accommodate for these

Conclusion

I know there are still many flaws in this system and many ways that it can be improved. This will do for now though and has scratched the creative itch I had. If you have any thoughts or critiques on the approach I took please feel free to reach out to me on X (Twitter).

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