In this curated analysis, we build a comparative, collaborative understanding of assumptions about “knowledge” in our different domain areas. These are not meant to sound like a cohesive “voice,” but rather punctuated snapshots from each of us. By anchoring our work in a shared analytic question, we create a common frame that allows differences and resonances to surface without forcing consensus. This approach reflects the value of “explanatory pluralism” embedded not only in the data publishing software we leverage (Poirier 2017), but also in our collaborative method itself.
We each answered the question first individually about our own cases and then we came together for a synchronous discussion to tease out the shared learnings and insights across domains. The summary below includes our collective summary of insights across vastly different topical areas in the "Database as Book" as well as our individual responses.