Just wrote a short summary of my method to a friend. Might not be terribly readable for people who haven't used Roam, so take it for what it's worth. Hope it's

Just wrote a short summary of my method to a friend. Might not be terribly readable for people who haven't used Roam, so take it for what it's worth. Hope it's for some use :-) What I do is an interaction between the following: Article <-> Tags <-> Hypotheses <-> Synthesis <-> Prediction <-> Research So I might read an article, then tag the article/figures with the relevant tags. If it's for a specific project, I keep a list of tags on a separate page. This ensure that I use the tags consistently, so that I can find all the relevant articles later. I purposefully keep the tags general, like "psychiatric conditions" rather than "depression, mania, schizophrenia" etc. When I reach the hypotheses page, this means that I can form relatively general hypotheses, and then nest them into gradually more specific hypothesis that are specifically supported by the articles. Then, I use those hypotheses to form new predictions. These predictions turn into new research questions, which I either explore via the literature or doing my own experiments. An example of this might be: "Wood 2018" <-> #Procedural Memory #Habits <-> Habits are part of procedural memory [[H]] <-> Habits are part of procedural memory [[H]] & Procedural memory is stored in the basal ganglia [[H]] <-> Damage to the basal ganglia disrupts habits [[H]] <-> Seger 2011 This affords me a lot of flexibility in total processing time; I don't spend a lot of time forming hypotheses that aren't interesting/necessary for me, I can quickly tag a lot of sources, and I can quickly collate those sources on a specific topic when necessary. You might say that the first half of the workflow is "induction", the second half "deduction and confirmation". I would love it if you had any questions or comments, but just writing this up has been useful for me as well.