Integrate R scripts

`message_data` contains some modules that are partly or entirely in R. For instance:
- The DLE code is entirely in R.
- The Nexus (water) code is partly in Python, but with data processing scripts in R.

This issue is to **discuss approaches** so that this code (a) can be integrated into complete workflows that run unsupervised, and (b) can be more reusable, in a standard way. The implementation should be in message-ix-models.

Some ideas:
1. Provide a CLI command like `mix-models r-script foo/bar/baz` that will simply invoke a file at (e.g.) `message_data/foo/bar/baz.R`, while providing some standard environment variables that the script can use to understand paths to data, etc.
2. Use [`rpy2`](https://rpy2.github.io/doc/v3.4.x/html/introduction.html) (with documentation & demo code) in Python code to directly call functions from R code in particular files, and retrieve its output for further processing.

Start by reviewing the existing DLE and Nexus code in message_data, including the R data-processing scripts, and inspect pull request #58. Compare the proposed CLI invocation with the rpy2 approach against the goals of unsupervised workflows and reusable standard integration; done requires a decided approach and its implementation in message-ix-models.

Written by the indexing model from the issue text.