Additional datasets to use

[cvitolo]

Finding interesting datasets to showcase algorithms can be very difficult.

One option could be to use ECMWF and Copernicus data. If you are not familiar with them, ECMWF stands for European Centre for Medium-range Weather Forecast, it is an inter-governamental organisation and stores the largest meteorological data archive in the world (global coverage). Copernicus is a European programme that provides satellite and in-situ observations for a number of domains (e.g. biodiversity, environmental protection, climate, public health, tourism, etc.).

There are countless uses for these datasets!

[Robinlovelace]

These sound like ideal candidates for the more advanced chapters, especially chapter 8 on rasters. Thanks for the links.

[Robinlovelace]

A big dataset on bikes from Holland: http://www.bikeprint.nl/fietstelweek/

[Robinlovelace]

Heads-up the Copernicus data is covered here: https://geocompr.robinlovelace.net/read-write.html#geographic-data-packages

Does that section cover the kind of thing you were thinking? Not mentioned ECMWF yet, can still do so if will be of benefit to lots of readers.

[Robinlovelace]

Closing for now. If anyone thinks of any more 'must include' datasets let me know but I think most of them are covered in https://geocompr.robinlovelace.net/read-write.html