Where can I find a sample of data with a known entropy to see how well NIST SP 800-90B does on it? I'd like a sample of true random data from a source that has a known entropy.  It's not easy to even produce true random data in sufficient quantity --- much less know the entropy of the source.  For instance, my only chance at grabbing true random data is waiting for /dev/random.
I'm spinning my hard drive and using the system as hard as I can to feed the kernel with enough entropy.    Meanwhile I'm collecting data up to 1,000,000 so as to satisfy NIST SP 800-90B because I'd like to estimate the entropy of /dev/random using the state of the art in entropy estimation.  (I'm aware of various problems with NIST SP 800-90B, but I have not found anything better out there that has been received the due scrutiny from the scientific community.)
How am I spinning my system?
$ while true; do sudo find /; done

How am I collecting the data?
$ cat /dev/random &gt;&gt; random.bit

Why am I not collecting it quickly from /dev/urandom?  Because that does not make sense.  I'd like to estimate the entropy.  I won't get more entropy from using a PRNG to process true random data.  As far as I can tell, using a PRNG might just make it harder for the estimators.  (Any thoughts on that?)
Do you know of any sample of random data out there that has a respectful entropy estimation that I can use to see how well NIST SP 800-90B does on it?  Is there any work done that states the entropy of Linux's /dev/random?
The question really asks for a sample of data from a source with a known entropy rate.

I suggest starting with the simplest: sources with zero entropy rate. Examples from which the first megabytes can be readily obtained:

a source producing only bytes at zero.
a source cycling over the 256 bytes incrementally.
a source consisting of the SHA-256 hashes of bytestrings of increasing length, in lexicographic order.
/dev/random or /dev/urandom modified to replace the input of their built-in PRNG with zeroes.
a source producing the bytes of $\pi$ (e.g. using Bellard's method).

NIST SP 800-90B tests won't help distinguish the last three from a source with some entropy. That illustrates these (or similar) tests can't reliably detect even a total lack of entropy, unless some hypothesis is made on the nature of the source.

We can use a lightly conditioned source. It's easy to make one from a microphone in front of something emitting noise (a fan will do), sampled by an ADC (sound input of a PC will do), and the bytes from some number of samples fed thru some light conditioning (like: group $n$ 16-bit samples and output the sum modulo 256 of the $2n$ bytes). That's a better fit for what NIST SP 800-90 is designed to work on. It'll be interesting to see how the gain of the microphone preamplifier, the position of the microphone, and parameter $n$, all influence the results. This source doesn't have a known entropy rate, though.

We can manufacture a source with biased but (presumably) independent bytes and a known biased distribution leading to (at most) a certainly known entropy. One way is to take /dev/urandom (or any source which output can't be discerned from that of a perfect true random source), group bytes by two to form an integer in $[0\ldots2^{16})$, and output the high-order byte of that unless the integer is less than $k$, for some parameter $k\in[0\ldots2^8]$. This leads to a source with byte zero having probability $(2^8-k)/(2^{16}-k)$, and the others $2^8/(2^{16}-k)$. Entropy in bit/byte is easy to compute as a function of $k$, and goes (for $k$ up to $100$):