write up design principles for hoad

[maxheld83]

it just occurred to me during the call with @kjgarza that it might be a good idea to write down the draft design principles for hoad that we've been talking about.

There are three levels of user/target segmentation, which correspond to three levels of our code.

1. Distributed in-memory database.
   This database should be as generic as possible, in the extreme case just duplicating the crossref coverage, but with a lot better performance and arbitrary SQL/dplyr queries.
   • Target: Analysts (us).
   • Code:
     • setup of the database (currently Google BigQuery, maybe Azure Synapse)
     • batch jobs to seed the db with dumps and incremental updates
     • example queries
2. Domain-specific APIs
   Opinionated queries against 1 to yield domain-specific data objects (that fit into laptop memories).
   A set of (multiple!) tidy data frames that make sense for hybrid open access uptake analysis, i.e. make it possible to run the plots/analyses in 3.
   • Target: R users interested in hybrid OA.
   • Code:
     • dplyr/sql queries against 1
     • additional on-client data wrangling
     • assertions and tests
3. Dashboard
   Views on the data in 2 to tell answer our business questions.
   • Target: HOAD project stakeholders
   • Code:
     • plots (those are also part of the package proper)
     • dashboard (maybe modules are also part of the package)

[maxheld83]

this is just quickly jotted down, should be in the repo somewhere