Choosing an open license 🏗️
Reusing other researcher's work is inherent in science. Licensing plays a central role for reuse, so we should know how it works. |
In my workshops on open and reproducible research licensing often comes up as a topic of fear. What am I allowed to do? Should I better let the legal department decide? How do I avoid going to jail? Most of the time choosing a license is actually quite simple. So let me help you loose your fear of it! 🤗 Choosing a license for texts, data, media, ...I really like the Creative Commons licenses for most research outputs (and other things I produce, like this newsletter). They are easy to understand and to pick. On the CC-website you can find a simple tool to help you choose your license. In research we want to almost always use the CC-BY or CC0 license.
Why not non-commercial? CC-BY-NC is another license I often see used, but I do not like it in the context of research. Why? The "NC" for non-commerical prohibits commercial use for anyone but the owner. That means, for example, that educators (like me) cannot use it, if there are fees or commercial learning platforms involved. Even blogs and Wikipedia struggle with NC if there are commercial derivatives or components. Read more here. Choosing a license for softwareSoftware needs specific licenses. So for software there is another website you can use for choosing a license. Again there is a license that works for most open projects: the MIT license.
That seems pretty simple, right? For more complex situations and when you have to worry about license compatibility of your code with software components that you use, please check out:
OtherFor other licenses, such as for hardware, choosealicense.com also has help for you:
I hope this short intro to licensing was helpful to you! Please note that I am not a legal expert but a self taught open science enthusiast. In other news
Glad to be ending today's newsletter with true faith in the scientific community 🙌 (not in the institutions that would not support their own researchers 🤷♀️). All the best, Heidi P.S. If you're enjoying this newsletter, please consider recommending it to your friends 💟. This really helps me with this passion project! Just forward it or send them the sign-up link: heidiseibold.ck.page
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Heidi Seibold, MUCBOOK Clubhouse, Elsenheimerstr. 48, Munich, 81375 |
Dr. Heidi Seibold
All things open and reproducible data science.
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