How to Organize Technical Research?


64 million scientific papers have been published since 1996 [1].

Assuming you can actually find the information you want in the first place—how can you organize your findings to be able to recall and use them later?

It’s not a trifling question. Discoveries often come from uniting different obscure pieces of information in a new way, possibly from very disparate sources.

Many software tools are used today for notetaking and organizing information, including simple text files and folders, Evernote, GitHub, wikis, Miro, mymind, Synthical and Notion—to name a diverse few.

AI tools can help, though they can’t always recall correctly and get it right, and their ability to find connections between ideas is elementary. But they are getting better [2,3].

One perspective was presented by Jared O’Neal of Argonne National Laboratory, from the standpoint of laboratory notebooks used by teams of experimental scientists [4]. His experience was that as problems become more complex and larger, researchers must invent new tools and processes to cope with the complexity—thus “reinventing the lab notebook.”

While acknowledging the value of paper notebooks, he found electronic methods essential because of distributed teammates. In his view many streams of notes are probably necessary, using tools such as GitLab and Jupyter notebooks. Crucial is the actual discipline and methodology of notetaking, for example a hierarchical organization of notes (separating high-level overview and low-level details) that are carefully written to be understandable to others.

A totally different case is the research methodology of 19th century scientist Michael Faraday. He is not to be taken lightly, being called by some “the best experimentalist in the history of science” (and so, perhaps, even compared to today) [5].

A fascinating paper [6] documents Faraday’s development of “a highly structured set of retrieval strategies as dynamic aids during his scientific research.” He recorded a staggering 30,000 experiments over his lifetime. He used 12 different kinds of record-keeping media, including lab notebooks proper, idea books, loose slips, retrieval sheets and work sheets. Often he would combine ideas from different slips of paper to organize his discoveries. Notably, his process to some degree varied over his lifetime.

Certain motifs emerge from these examples: the value of well-organized notes as memory aids; the need to thoughtfully innovate one’s notetaking methods to find what works best; the freedom to use multiple media, not restricted to a single notetaking tool or format.

Do you have a favorite method for organizing your research? If so, please share in the comments below.


[1] How Many Journal Articles Have Been Published?

[2] “Multimodal prompting with a 44-minute movie | Gemini 1.5 Pro Demo,”

[3] Geoffrey Hinton, “CBMM10 Panel: Research on Intelligence in the Age of AI,”

[4] Jared O’Neal, “Lab Notebooks For Computational Mathematics, Sciences, Engineering: One Ex-experimentalist’s Perspective,” Dec. 14, 2022,

[5] “Michael Faraday,”

[6] Tweney, R.D. and Ayala, C.D., 2015. Memory and the construction of scientific meaning: Michael Faraday’s use of notebooks and records. Memory Studies8(4), pp.422-439.’s_use_of_notebooks_and_records/links/5783aac708ae3f355b4a1ca5/Memory-and-the-construction-of-scientific-meaning-Michael-Faradays-use-of-notebooks-and-records.pdf

6 thoughts on “How to Organize Technical Research?

  1. The biggest advantage of online note storage is retrieval in a couple senses: able to access via (basically) any device anywhere (and when needed shared with others) and able to search through all notes. No matter how well structured you think your notes are, you still need to just ask, where’s my note about XYZ? and get it instantly.
    FWIW, I’ve been migrating from Microsoft OneNote to Notion (free tier) but am also a new user of a Boox/Onyx note taking device – just can’t beat being able to write down lecture notes free-form.

  2. Absolutely. When I returned to MacOS from Windows in 2015, my search time for text through the whole filesystem went from minutes to a fraction of a second. For me a total game changer.

  3. Darn, I was hoping you were going to make some specific recommendations. I’m shifting into technical research currently, so I’m grappling with this problem myself.

    Currently I’m using Zotero to track papers, a Google doc (at my mentor’s request) for chronological notes, and org mode for most other things (along with some colab and jupyter notebooks). But I’m not that happy with that setup.

  4. I also haven’t found a silver bullet for this problem. I’ve lately used spreadsheets and Google sheets for notes on papers read–I can see the full list of papers easily and can click the paper url or view my notes almost frictionlessly. For working on ideas I use large 24″ x 15″ sheets of scratch paper and multiple colored pens. Like Miro but quicker and more flexible. Many times I’ve worked out some algorithm implementation or talk outline on these large sheets in the most freeform way possible and then written something more well-crafted on paper or laptop. I’ve often thought about getting a reMarkable 2 tablet.

  5. I spent my early career as an R&D-focused engineer, working to turn scientists’ proof-of-concept lab experiments into prototype instrumentation. A huge problem was finding all the prior art available concerning the current project, to help ensure that any resulting instrument was worth turning into a product, independent of the validity and applicability of the in-house research.

    For me, a huge key was to track the tools used in papers by researchers in other domains. When I was working in image processing, the ImageJ tool (now wrapped in Fiji) was popular because of its good “bones” and the ease of adding new custom plugins. The best part is that folks put their DOIs in their source code comments!

    For example, I once found a key algorithm I needed for real-time neutron radiography in a paper concerning confocal microscopy. Google was useless to find such leads, but tracing the tools can tell the tale!

    These days, so much is placed in GitHub. Careful use of its search tools can yield more results with less effort than spending hours (or days) in Google Scholar.

    I organize such inter-domain results via free-form concept trees, such as supported by tools like Xmind, GitMind or Freeplane. While the same terminology is seldom used across domains, the concepts do link up.

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