I have a specific need, which is to do as little coding as possible to transform the dataset that you recommend to a format that our software can use.
We want to divide Europe (possibly, later, the world, but let's stick with Europe for now) into 30 arc-second cells, with 100x100 cells for one degree.
For each of these cells, we need the highest elevation above sea level for anything at all in that cell, to a one metre resolution.
I would imagine that I will find datasets with far too much data, and would like to make it is simple as possible to reduce that to what we want. I will code a Python script to do that.
I would guess that it would be simplest for me to parse a dataset with fewer data items – I do not need to know that names of towns, or where rivers or airports are, just the height of each point in the dataset.
A bonus would be if there exists a Python module to parse the data format of the dataset, but I can code it myself if not. Otherwise, simpler formats, like CSV or XML are preferred over more complex formats.
Any dataset MUST be freely available of commercial use and must NOT require us to publish our source code.
[Update] I can find a few datasets, and also the Google elevation API (https://developers.google.com/maps/documentation/elevation/start), but I can't find a dataset which gives me the highest point in each 30 arc-second cell :-(