Questions-Claim-Evidence/Discourse Graph in Obsidian?

Has anyone ever tried to implement Joel Chan’s Discourse Graph workflow in Obsidian, I guess using Dataview, maybe DB Folder etc?

Here’s a really nice demonstration of it in Tana: Advanced Note Taking in Tana with QCE! - YouTube

And Joel’s paper on it: Knowledge synthesis: A conceptual model and practical guide · Open and Sustainable Innovation Systems (OASIS) Lab

This is one of the reasons I (and quite a few people I know) never managed to fully make the leap from Roam to Obsidian, and why I’m currently tempted by Tana. But for many other reasons I’d actually rather be fully in Obsidian if I could get this working here. This workflow felt impossible/too hard to implement in Obsidian without a lot of friction though. Seeing how far some of the plugins have come, I’m guessing we might now be closer to managing something like the Tana example above.

Any thoughts/experiences?

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You can already build something like that using metadata-powered plugins (dataview, dbfolder, metadata edit, etc etc). Obsidian itself will improve its support for this in the future https://forum.obsidian.md/t/super-fr-enhance-obsidian-with-a-type-system-for-notes-and-database-like-views-metadata/46444.

I wanna add a note that is tool-independent about this workflow.
If you do follow QCE, or any other highly structured system for your notes, you are essentially condemning yourself to do the work every time you read/write something, categorize it appropriately in this database.

You are not paid for having a neatly organized vault.
You are making the assumption that this daily chore will pay off at the time of producing your output (for example a paper, a post).
You are banking that:
(Time Spent Keeping The Database Organized + Time Using the database to produce an output) < (Produce an output with an unorganized Vault)

I am very skeptical of this assumption. I am skeptical of frontloading the work, because you do not know if said work will even be useful in the end (how many reviewed papers will end up in the final product?). You don’t know if the paper you categorize today will be useful 2 years from now.

Example from a CS Task: sometimes you need to perform a search in a list that grows over time. Is it better to keep the list sorted as your receive datapoints or to just search the unsorted list?
Keeping the list sorted is a small chore to do every time there’s new datapoint, searching a sorted list is fast. Searching an an unsorted list is slow(er).
Which is better in the end? It depends on the access pattern.

Another two side points:

  1. The more structures you use, the more you tie yourself to a tool that can parse those structures.
  2. Even if I don’t technically blame structured data for this, there is a potential detrimental psychological aspect to it: the dread it can produce every time you have to add something or the discomfort you may feel when you fail to keep things neatly organized (because life happens).

Whenever I think to introduce structure, I try to figure out if it’ll be worth it.

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Is this an attempt to overthink it? In reality, QCE can just be linked notes for each element within Obsidian, that way, each note is useable across multiple contexts. ie, any evidence note could be linked to multiple claims etc.

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A Discourse Graph Extension as it exists in Roam Research would be of great interest! +1

If you do follow QCE, or any other highly structured system for your notes, you are essentially condemning yourself to do the work every time you read/write something, categorize it appropriately in this database.

The counterargument to this claim is that people who are doing knowledge-synthesis research projects need some way to organize their information anyway, and having three note types is not much more work than one note type, especially considering the potential benefits, so it is just as well to use a simple data model like QCE. But keeping it simple to reduce mental “friction” is good advice.

Joel Chan’s paper “Knowledge synthesis: a conceptual model and practical guide”, linked in the original post above, lists some of the potential benefits of the model:

  1. Effective synthesis: This model allows for rich layers of context to aid synthesis. Distinguishing between observation notes and synthesis notes helps prevent me from rushing too quickly to generalizations, and allows for careful, nuanced questioning of past claims (e.g., does X really not work?), and consideration of possible syntheses between opposing claims…”
  2. Reusability of ideas across barriers of time, people, projects, and disciplines: I believe this flexible compression not only helps synthesis right now, but also enables me to earn compound interest on the notes over time. One mechanism by which this happens is that the overhead for regaining context for my notes is reduced for my future self, and possibly for others as well, since the details are much more directly accessible through the three-part model. This is important, because the devil/diamond is in the details, and details fade over time from memory. I suspect that synthesis notes and systems that omit details (or at least make it hard to access details later), will have a much shorter half-life. A less obvious benefit of retaining context is an increased capacity to notice points for intellectual progress, since anomalies and inconsistent results can often be a pointer to where a conceptual breakthrough is most needed…”
  3. The ability to distribute the synthesis process: If I’m right that these sorts of notes are more shareable, then I should be able to distribute the process across a team of people. Hopefully this also means we get to substantially reduce the time needed to do effective synthesis. I am testing this hypothesis right now with my lab, and hope to get others to join me.”

Another way of stating these benefits is that it makes the reasoning process transparent via a shared schematic language in the structure of the notes, so if you give the notes to someone else (including your future self who may have forgotten what you were thinking when you took the notes), then that someone else will be able to make sense of them easily and see where more research needs to be done.

Chan’s QCE data model is similar to IBIS, another model that has been used for similar purposes for a long time (since the 1970s). For more info about IBIS in Obsidian, see the forum topic: Tips for making an issue-based information system

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