Atomic Notes for Personal Knowledge Graphs

I came across the work of Ivo Velitchkov on Personal Knowledge Graphs yesterday.  Some of it goes well beyond my current level of comprehension because of the technical aspects but I enjoyed the more conceptual elements and the history of the evolution of Personal Knowledge Management (PKM). 

Digging deeper into technology-enhanced notetaking made me question the way I take notes and whether I need to make better use of some of the more advanced functionalities of TiddlyWiki, and by extension, TiddlyMap.  In particular, transclusion seems to offer ways to create more atomic notes.  

For example, taking notes on a book I am reading in a single page or Tiddler) could result in a very long page with many different ideas.  I can tag the page with keywords but I want to be able to quickly reference specific elements of my notes.  I want to be able to quickly pull a specific visual.  The way to do that is by creating "atomic notes" that are then transcluded in the page for that book.  Each atomic note becomes a node in the graph, with its own properties and relationships to other nodes. 

Created by DALL.E:  Atomic Notes in the Context
of a Personal Knowledge Graph 4/24/2024.

This exploration into note taking also made me wonder whether it would be worth revisiting all kinds of paper-based notebooks I have accumulated over the years into my growing TiddlyMap.  The first notebook I came across is a small notebook meant to capture quotes.  I know I also have collections of quotes in other TiddlyWikis.  Bringing everything together (with a focus on the key themes I have already identified) would be a very integrative exercise.

Another question worth exploring is whether it would be possible to integrate personal knowledge graphs with enterprise knowledge graphs.  That is, to some extent, what the Microsoft Graph does and how Microsoft Copilot for M365 pulls content from individual employees' email, Teams, files, and combines that with whatever enterprise content the individual employee also has access to.  

What if there were a way to structure OneNote notebooks for atomic notes and a personal knowledge graph?  What if that personal knowledge graph could be integrated into an enterprise knowledge graph?  I am not suggesting that a personal knowledge graph be share with the enterprise.  I am only suggesting that an individual employee should have easy access to their own personal graph, the enterprise knowledge graph, AND external graphs (like Google's Knowledge Graph) through a single interface. 

White Spaces and Unknown Unknowns

I dug up some coloring books from the basement's collection of arts and crafts supplies dating from when my kids were growing up.  I needed something to occupy my hands and empty my brain.  Ironically, that tends to be when ideas show up unexpectedly.  

I was attacking my third drawing when suddenly the decision I had to make wasn't which color marker to pick, but whether or not to color the "white space".  The pre-printed lines clearly show shapes and the brain immediately interprets the area between lines as something to be colored.  This happens even with geometric shapes or lines that don't represent a recognizable object.  Of course, one could decide to leave some of those shapes uncolored, but that means they are intentionally left white.  What I was wondering about was whether or not to color the white space that corresponds to "empty space" or negative space.  

In cognitive science, this relates to selective attention.  Our brain focuses on certain stimuli while ignoring others.  We notice some things and miss others.  Refocusing my attention to the empty spaces was a way to alter my focus and consequently, my perception of the image I was coloring.  I refocused on the negative space. This is somewhat similar to or related to the concept of unknown unknowns, the things we don't know we don't know.  We're oblivious to our own blindness and ignorance.  

What am I not seeing?  What am I missing?  How could I see differently?

Explorations and Discovery: Looking for Adjacent Content

Exploration is more than just discovering what we agree with; it's about pushing boundaries and challenging our perceptions.

The words exploration and discovery go well together.  If you start on an exploration journey, you are likely to make some discoveries.  It's even a little more exciting than going on a learning journey and collecting some lessons. Words matter.

Today I discovered someone I now want to follow because what I read from that person resonated strongly.  This is part of the problem.  We tend to read and follow what resonates, what we agree with, which leads to reading more of the same people who write things that resonate with us, which only reinforces our opinion of ourselves and allows us to dismiss everything else either as crazy or just noise.  

I would like my explorations to lead me to things that are adjacent to what resonates with me, to push the boundaries a little, to expand the zone of what resonates with me to what makes me think and rethink.  

I am particularly interested in this discovery because it will expand my thinking.  I discovered Joan Westenberg's blog and other writings.  I discovered her via Harold Jarche's blog.  Harold Jarche is already on the edge of my comfort zone and someone I have followed closely for a long time around Personal Knowledge Management.  Joan Westenberg is pushing things in the same zone of discovery.

What's the point I am trying to make?

In an attempt to curate interesting, relevant information, and to support my explorations for valuable discoveries, I need to strategically pay attention beyond what immediately resonates with me and notice the adjacent content that can take my own thinking one step further. 

2024 Explorations - Q1 Review

I started my 2024 Explorations in January. It was meant as a combination of two main objectives:

1) a learning framework or learning agenda, not so much to ensure that I would engage in continuous learning but more to ensure that my continuous learning was adequately focused on some key themes of interest;

2) using technology, and more specifically TiddlyMap, as a personal knowledge management tool that would allow me to experiment with (a form of) knowledge graph.

We've reached the end of the first quarter of 2024 and so far so good. I just completed a quarterly review of progress and generated a few insights.

• Is TiddlyMap allowing me to really learn about knowledge graphs? Yes, but as expected, it has its limitations. I will eventually crash the tool. I don't think it is meant as a graph database but it works well as an exploratory tool. Ultimately I need to move my data to a real knowledge graph tool like Neo4J. That should be a goal for the second quarterly. I started learning more about Neo4J, including learning the basics of Cypher.
  
  
• Is my learning framework working? The main themes and topics have proven very useful as guardrails and as an organization schema both for my thinking and for capturing notes. There are some issues with the taxonomy. Some topics are overlapping and I keep wanting to create more tags. So far, I have limited the number of additional tags and I have only made minor adjustments to the topic tags. Proliferation of tags would lead to inconsistencies. Until the tagging is automated, the number of tags is limited by my capacity to remember them all.
  
  The maps are telling me something pretty clear. I have focused perhaps 80% of my efforts on the AI and Knowledge Graph topics. The maps related to those topics are very large, which has enabled me to test filters. Like a search returning too many results, a map showing too many relationships is unreadable. For other topics, I have collected and curated resources, but I have not spent time connecting the dots. As a result, the maps are less interesting (so far).
  
  
  

• Is the basic ontology working? Yes, but the value of TiddlyMap's automated functionalities has made it much more powerful to create maps based on what TiddlyMap does with relationships based on tags and links associated with Tiddlers than to manually create a specific set of relationships based on my simple ontology. I have learned most by manipulating the filters to understand how relationships are displayed. Interpreting the resulting maps for potential insights is the next stage I want to dive into. Since I am the one creating all the links and the tags, the maps are not telling me anything I didn't already notice, but they are representing the connections visually and often reminding me of connections I made weeks ago that I don't hold in immediate memory.  I posted one of the maps in the Insight Maps section. 

The biggest ha-ha moment was related to tagging. I was using the tagging functionality to tag too many different types of things and failing to use a major functionality of the tool. I realized after a while that I should be using the fields to document the properties of a node. For example, "author" is a field rather than a tag. This allows me to have a consistent set of node properties and to rely on tags only for topics and some of the metadata used for navigation purposes. This also really helped make the maps more meaningful.