which enables more agile and evolving [[ontologies]]. - People in the [[Hackers]] community are actively working on ways to manage aliases and merging. - People also use [[bi-directional links]] to do [[Contextual Bootstrapping]] of ideas, creating "empty pages" or "hooks" for concepts. - ^^The hackers^^ [[Hackers]] - Others?? - ^^The wanderer?^^ - Where many people are - Moves between many things, in constant flux - Some high-level takeaways: - Many of these in isolation are not new! Lots of beautifully detailed work in [[active reading]]; see as far back as #[[@oharaStudentReadersUse1998]] for rich examples, or even… as far back as [[Charles Darwin]] and, arguably, as old as external representations ;). What we see here is a different lens with which to view these data, to consider what these behaviors (could) do. - The sophistication of the system (vs. the medium or tool) might explain [[Z: The stubborn effectiveness of analog media]] - Why are they doing this? - They want to do this work (better), but often don’t because it ends up being too costly - But the social context is key for at least some of it: a lot of explicit work being done in collaborative settings - Advisor meetings - Large-scale collaborations - Teams - Strong opportunity for progress by partnering modeling and standards work with growing user interface innovations (sort of the reverse of making [[semantic publishing]] user interfaces better). - Examples - https://twitter.com/MuseAppHQ/status/1273698452539609088 - See also [[sys/Hypothes.is]] - Different kinds of questions: - which types of annnotations at which points might be valuable for the user to formalize / contextualize in some way? - how might formalisms of [[semantic publishing]] deliver immediate value to the scholar at different parts of their scholarly workflow? - identify some of the frictions and pain points in their process. good clue to this is what motivates the move to [[QDAS]] and [[sys/LiquidText]] - quotes from guided tour in [[John Thesis]]? - how much of this is actually happening? is there a way to study this in a way that is analogous to the [[cognitive surplus]] idea from crowdsourcing? - see, e.g., What is the scale at which scientists are producing annotations and notes? In other words, what is the untapped opportunity here? What is the "drag coefficient"? How much energy is being "wasted’?