Open and Sustainable Innovation Systems (OASIS) Lab working notes

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🌲 zettels

Meta: public



Synthesis is sensemaking

Scholarly synthesis is problem framing

Synthesis is learning

A causal model is a kind of synthesis

Interdisciplinary synthesis must integrate diverse evidence

systematic reviews are a narrow subset of synthesis

systematic reviews are infrequently updated, despite often being outdated very quickly

Writing review papers is impactful but discouraged


Claims are a usefully granular unit of knowledge reuse in design

Atomic statements are a fundamental unit of scientific discourse

Decontextualized knowledge is easier to store and refind


Requiring formalism in interactive systems can be harmful

[[Z: incremental formalization can mitigate risks of formalism in interactive systems]]

People are reluctant to formalize

Tacit knowledge cannot be formalized

Interactive systems that require formalism frequently struggle with user adoption

Useful structures and formalisms vary significantly across people, situations, and tasks

Fundamental ontologies of disciplines change as the disciplines evolve

Ontologies create an unhelpful illusion of consensus and certainty

Information work

People very frequently search for articles they have found before

Citation is a noisy signal

Scientists often cite to...

Most systematic reviews are done by temporary volunteers

Many systematic reviews are done in an ad-hoc mix of tools

Researchers today spend less time reading each paper than in the past

Researchers today read more papers than in the past

Researchers today read more than twice as many different journals as they did in the past


Most private annotations are not useful to other people

Notes are boundary objects

Scientists repurpose qualitative data analysis software to do synthesis


There is a small and finite set of sensemaking representations

People start making sense of large collections by forming temporary clusters

Data extraction is the main cost of sensemaking

(up to 75% of total time needed)

Scientific systems

Ghost theories hinder scientific progress

Bullshit is very adaptive in environments with noisy and costly evaluation

Leeway is a critical enabler of interdisciplinary work

Intellectual lineage constrains the questions scientists ask


Information is often fragmented across media

People like folders

People often spend most of their 'thinking' time getting into a position to think

Piles of documents often have well-defined semantics

The process of capturing information may be more valuable than the information that is captured

Referenced in

April 21st, 2020

roamhack How do we write 🌲 zettels (evergreen-notes) for time-bound understandings, which are very common in problem formulation (up till now, we lack X, or have focused on Y...)?

about these notes

If you're pondering similar ❔ questions as I am, and/or have new references or ideas that might connect to one or more of my 🌲 zettels, I'd love to hear from you!

Z: How can we best bridge private vs. public knowledge?

But also possibly because a lot of what we do in terms of externalization is Epistemic Action that *is* thinking in the moment, not necessarily producing a record that will be in any way useful after the moment. 🌲 zettels

🌲 zettels