Choosing a software license

Objectives

Copyright and derivative work: Sampling/remixing

[Midjourney, CC-BY-NC 4.0]

[Midjourney, CC-BY-NC 4.0]

Copyright controls whether and how we can distribute the original work or the derivative work.
In the context of software it is more about being able to change and distribute changes.
Changing and distributing software is similar to changing and distributing music
You can do almost anything if you don’t distribute it

Often we don’t have the choice:

Can we distribute our changes with the research community or our future selves?

You find some great code that you want to reuse for your own publication.

This is good for the original author - you will cite them. Maybe other people who cite you will cite them.
You modify and remix the code.
Two years later … ⌛
Time to publish: You realize there is no license to the original work 😱

Now we have a problem:

😬 “Best” case: You manage to publish the paper without the software/data. Others cannot build on your software and data.
😱 Worst case: You cannot publish it at all. Journal requires that papers should come with data and software so that they are reproducible.

Comments:

Arrows represent compatibility (A -> B: B can reuse A)
Proprietary/custom: Derivative work typically not possible (no arrow goes from proprietary to open)
Permissive: Derivative work does not have to be shared
Copyleft/reciprocal: Derivative work must be made available under the same license terms
NC (non-commercial) and ND (non-derivative) exist for data licenses but not really for software licenses

Great resource for comparing software licenses: Joinup Licensing Assistant

Exercise

Discussion

Our example code uses the libraries scikit-image, scikit-learn, numpy, matplotlib, and pywavelets. Do we need to look at their licenses? In other words, is our project derivative work of something else?