NumPy serves many kinds of users....The challenge: provide ways to guide those users to the parts of the documentation most relevant to them.
I have a thought on how to approach this. We know many of the communities NumPy serves; let's next identify (for ourselves, not the proposal) what each of them needs. It could be as simple as: *Educator* - knows... - needs to know... *Researcher* - knows... - needs to know.. A table like that would be useful for self-assessment and planning. It helps answer questions like: - Which communities are we most shortchanging right now? - Which communities do we feel most strongly about (our largest base, most disadvantaged, etc.)? - If doc D is our next doc, does it help those communities? Or maybe we want to go round-robin through communities with each new doc. - What assumptions can a writer make about audience background? We're also then equipped to bring user categories out to a web page and meet the big-tent challenge head-on, with links like: - If you're an educator... - If you're a researcher... each one taking the user to an Educator, Researcher,..., page containing links to the information they're most likely to want.