Norway has two separate official languages. They are unusually close - one is relatively close to Danish, and the other started as a collection of dialects, but technically they are written languages, especially Bokmål which basically means "book language".
I'm unusual in that I speak close to "pure" Bokmål. Thanks to expectations at school etc., a lot of speakers who write Bokmål will adjust or tone down their dialect if asked to read a text that is written in grammatically and orthographically correct bokmål, but will otherwise speak in a manner that can deviate fairly significantly from the written language.
As such, depending on whether your goal is text to speech or speech recognition, the pronunciation you will need is very different.
E.g. people I know who write Bokmål might say something like "hva erredu ser på a?" ("what are you looking at?") with hardly any gaps between words, while I would stick close to the written "hva er det du ser på?" with clear gaps. In recognition you need to handle both (and many other variations), while for generation you'd at least by default usually want the latter unless there are indications the text is written in dialect.
It strikes me you'd really want people to write more detail about what it is they are speaking and/or let people tag/label data with additional info about accents. Not just for this, but for other multi-lingual speakers as well. E.g. it'd be helpful to have many foreign accents in the English (and other languages) dataset for recognition, but as much as I want speech recognition to understand me, I'm not particularly interested in teaching it to speak English with a strong Norwegian accent.
That is less of an issue than the dialects in some languages that can involve much more than just speaking the same words differently.
To take another example "Jeg åpnet døren og gikk ut i solen" og "Jeg åpna døra og gikk ut i sola" are both valid Bokmål. Depending on context a reader may stick strictly to the text or swap åpnetåpna, dørendøra, solasola, and every permutation is valid. Which exact set you use differs and some speakers will write one but use the other when speaking. E.g. I would say åpna, døra, sola, but write åpnet, døren, solen. The latter is more formal and/or old-fashioned in some parts of the country, but the perception of that also varies by region. And this totally leaves out all the dialect variations used by people who'd say their language is Bokmål, and would be recognized as such by Norwegian speakers, but who use variants of words or conjugations that aren't technically recognized as valid Bokmål.
The former is more "modern" (several of the forms are only valid Bokmål as a result of successive language reforms), more common in the Eastern part of Norway outside of the posher parts of Oslo and other wealthy regions, and (weirdly) more common in 1970's radical left-wing academics (especially people involved with the Maoist Workers Communist Party/AKP-ML) as an affectation/sociolect, with each of these groups also deviating in other aspects....
If you want to maximize the utility of a dataset like this, you really would want to let each speaker at least assign a lot of tags/labels to their profile; even if you don't want to deal with the hornet nest of trying to figure out all the distinctions, even unstructured labels would be a start, and ideally allowing people to tag individual recordings as well, because there are a lot more variations than just "language" and "accent" here.