Nice idea @orbmis, geographical diversity is important indeed.
With the crawler we have at MigaLabs, we can get the country of most beacon nodes we connect with, but as @Izzy mentioned that does not tell us whether that node has validators connected to it or not. However, we also have other extra information. For instance, beacon nodes also share which attestation channels they are interested in. If you are a beacon node without validators, most likely you will avoid the extra work of listening and forwarding messages on more channels than the ones you really need. Beacon nodes attached to validators do need to listen to the attestation networks required to validate blocks according to their respective duties. So if we cross these two datasets, we can already have an idea of the geographical distribution of validators.
In addition to this, we can also look at things like whether the node is a cloud node or a residential node, which we can also derive with a relatively high degree of confidence.
What I would suggest is to implement both strategies in parallel and keep them independent, and then when we get some first results compare both distributions. I would be happy to have my team working on this.
What do you think?