Hi Jean, > After a while user will get a subset of highly ranked headings in their > corresponding Org files. That subset then can be used as quick bookmarks or > get bound to keys.
This is a higher tier of PIM than Textmind. Textmind is for processing thoughts. For example, I use it to convert these email exchanges into useful notes and documentation. Crystallized knowledge that needs to be optimized for rapid or lateral access belongs in a PKM or CRM app. There are many options, and which is best likely depends on the specific use case. (Assuming it doesn't belong in Postgres or Pubmind.) > From other people's experiences I can see they are thinking different. It is > questionable if there is one algorithm corresponding to many people's natural > thinking. Almost nobody has a holistic natural thought algorithm. An algorithm has a strict definition, whereas biological thought is evolved and messy. > But I cannot access image related to business ABC that is located in 2004 > quickly unless such image is indexed somewhere by its meaning, maybe "boat > purchased" would be meaning related to such picture. Then if I wish to see > boats I have purchased I would type most probably "boat" and from there find > various other attributes such as dates, types and similar. Images should have a creation date in metadata and also some tags, I agree. Whether to organize them in a Binmind using 10 Bins is a matter of taste. I prefer to keep them in 10 Bins until their tag nomenclature is mature. Then, when worthwhile, I would move them to a dedicated image management app, and add a good set of tags and metadata to ensure they won't be lost later. If the app allows it, I might still organize the pics into a tree, just to make it easier to navigate the whole collection without repetition, and understand its primary meaning quickly. This extra work is profitable only for high-value images. The existence of the tree permits continued nomenclature evolution without risking some images getting lost due to tag drift and rot. Treemind is good at nomenclature evolution via Rapid Inductive Iterative Tree Refiling.
