7 Matching Annotations
  1. Apr 2022
    1. It is difficult to see interdependencies This is especially true in the context of learning something complex, say economics. We can’t read about economics in a silo without understanding psychology, sociology and politics, at the very least. But we treat each subject as though they are independent of each other.

      Where are the tools for graphing inter-dependencies of areas of study? When entering a new area it would be interesting to have visual mappings of ideas and thoughts.

      If ideas in an area were chunked into atomic ideas, then perhaps either a Markov monkey or a similar actor could find the shortest learning path from a basic idea to more complex ideas.

      Example: what is the shortest distance from an understanding of linear algebra to learn and master Lie algebras?

      Link to Garden of Forking Paths

      Link to tools like Research Rabbit, Open Knowledge Maps and Connected Papers, but for ideas instead of papers, authors, and subject headings.

      It has long been useful for us to simplify our thought models for topics like economics to get rid of extraneous ideas to come to basic understandings within such a space. But over time, we need to branch out into related and even distant subjects like mathematics, psychology, engineering, sociology, anthropology, politics, physics, computer science, etc. to be able to delve deeper and come up with more complex and realistic models of thought.Our early ideas like the rational actor within economics are fine and lovely, but we now know from the overlap of psychology and sociology which have given birth to behavioral economics that those mythical rational actors are quaint and never truly existed. To some extent, to move forward as a culture and a society we need to rid ourselves of these quaint ideas to move on to more complex and sophisticated ones.

    1. doi: https://doi.org/10.1038/d41586-021-02346-4


      Oddly this article doesn't cover academia.edu but includes ResearchGate which has a content-sharing partnership with the publisher SpringerNature.

      Matthews, D. (2021). Drowning in the literature? These smart software tools can help. Nature, 597(7874), 141–142. https://doi.org/10.1038/d41586-021-02346-4

    2. Open Knowledge Maps, meanwhile, is built on top of the open-source Bielefeld Academic Search Engine, which boasts more than 270 million documents, including preprints, and is curated to remove spam.

      Open Knowledge Maps uses the open-source Bielefeld Academic Search Engine and in 2021 indicated that it covers 270 million documents including preprints. Open Knowledge Maps also curates its index to remove spam.

      How much spam is included in the journal article space? I've heard of incredibly low quality and poorly edited journals, so filtering those out may be fairly easy to do, but are there smaller levels of individual spam below that?

    3. Amie Fairs, who studies language at Aix-Marseille University in France, is a self-proclaimed Open Knowledge Maps enthusiast. “One particularly nice thing about Open Knowledge Maps is that you can search very broad topics, like ‘language production’, and it can group papers into themes you may not have considered,” Fairs says. For example, when she searched for ‘phonological brain regions’ — the areas of the brain that process sound and meaning — Open Knowledge Maps suggested a subfield of research about age-related differences in processing. “I hadn’t considered looking in the ageing literature for information about this before, but now I will,” she says.
    4. Another visual-mapping tool is Open Knowledge Maps, a service offered by a Vienna-based not-for-profit organization of the same name. It was founded in 2015 by Peter Kraker, a former scholarly-communication researcher at Graz University of Technology in Austria.


      Open Knowledge maps is a visual literature search tool that is based on keywords rather than on a paper's title, author, or DOI. The service was founded in 2015 by Peter Kraker, a former scholarly communication researcher at Graz University of Technology.

  2. Mar 2022
    1. There are some additional interesting questions here, like: how do you get to the edge quickly? How do you do that across multiple fields? What do you do if the field seems misdirected, like much of psychology?
      1. How do you get to the edge quickly?

      I think this is where literature mapping tools come in handy. With such a tool, you can see how the literature is connected and which papers are closer to the edge of understanding. Some tools on this point include Connected Papers, Inciteful, Scite, Litmaps, and Open Knowledge Maps.

      1. How do you do that across multiple fields?

      I think this requires taking an X-disciplinary approach that teeters on multiple disciplines.

      1. What do you do if the field seems misdirected, like much of psychology?

      Good question. It is hard to re-orient a field unless you can find a good reason (e.g., a crisis) for a paradigm shift. I think Kuhn's writing on [The Structure of Scientific Revolutions(https://www.uky.edu/~eushe2/Pajares/Kuhn.html) may be relevant here.