Happy to - I propagandise both pieces of software in each other’s forums! TB is a weird and opinionated piece of software, the likes of which I’ve never seen elsewhere. I both love it, and wish it was completely rewritten, but realise that what makes it is that it’s the unique vision of its author. It’s what pushed me into the Apple ecosystem originally.
So for writing, no, I barely use the map view.
For thinking, I use it all the time. I remember positions of things more than anything else, so when I’m putting ideas together the spatial layout is really key for my sense of understanding. Trivial as they sound at first, the adornments in map view are hugely useful in clustering thinking and ideas, more than depth - I find depth in maps more useful for aggregating evidence around distinct notes.
In my writing, I scribble notes-to-self in the markdown surrounded by {}
- so I have {todo:flesh this out}
, {cite:find source}
, {q:check structure}
, and some agents in TB that scurry through my outline and pull classes of notes into other notes, linking back to them - so one with the prototype for this finds anything {q:...}
and pulls the text out into child notes and links back, another looks for {xyz:...}
notes, and so on. It means I can hammer words out in plain text, leave myself notes, and then have them all collated later. This I view through the map view, as the nested elements make visual sense then; but otherwise, yes, it gets too fiddly to see what’s inside them. I remember a much older TB handling this better, but visual emphasis shifted elsewhere.
I also use MindNode, but to be honest, it’s a very prescriptive visual layout engine. It makes very slick and mac-like diagrams, and the integration has its’ place, but I find TB much more fluid and open for building maps for thinking and associating supporting information around them.
Day-to-day, I’m mostly in outline view, with a separate tab and branch in timeline view, and other tabs with map views for document management and reviews (the {}
discussed above).
And @rkaplan, without going too deep, it’s a critical data studies take on social media data used in research and policy making; that it’s both seductively easy to get, but intrinsically misleading when ‘sampled’.