Because nothing meets that standard, it's not an applicable measure of quality. Also, it tends to lead to binary thinking: 100% or null.
But we live in a world of less than 100%, and there is a lot of variation: Five nines, 80%, datasets with just a few valuable records, etc. That's where the real-life questions are.
If you spend any time on either OpenStreetMap or Google Maps in the rural US, and you are very likely to find both missing streets, and streets that have been completely hallucinated out of nothing -- mostly because they were both originally sourced from the US CENSUS TIGER data -- a US govt data set that tends to be full of errors.
OpenStreetMap contributors of often improve these issues over time (though it largely depends on if the area you care about has some sufficiently dedicated mapper).
None of the above. People might just be curious and interested!
Thanks for sharing all that. I didn't know much about the quality. Much crowd-sourced data has accuracy problems.