Comments (14)
from textbook.
See also #59
from textbook.
I just ran into this when I browsed Matthew Brett's fork of this material, and noticed that he had to branch from 64b20f0 because of the license change in 710ed4e.
/cc @papajohn
from textbook.
This is up to John & Ani, who wrote almost all of the material in the textbook.
from textbook.
@stefanv or @matthew-brett out of curiosity, do you have an idea for a license that would be less-restrictive that could still work. I believe that the original authors wanted to make sure that others wouldn't modify the content and still call it "the data 8 textbook" etc, and that the original content would be tied back to the Data 8 course. I agree the current version is too restrictive, but what would be a good alternative?
from textbook.
I can tell you what I prefer - which would be CC-BY (ideally) or CC-BY-NC (if CC-BY is not acceptable for some reason).
With the current license, I think y'all are giving up on the chance to be the starting point for many data science textbooks, with associated attribution. Y'all may even get benefit from the various edits. There will surely be many textbooks, and soon, and it would be a great benefit, if we teachers could have a common starting point. If we start here, then we have a really good foundation:
- standardizing on Jupyter notebooks
- I really like the jump-into-the-deep end approach to the start of the course
- data tables and arrays at the beginning
- resampling as the foundation for inference
- emphasis on optimization
- high quality build system for the textbook, with community support as the system gets adopted.
The teaching material is really really good. In many cases, it's hard to see how writing something different, could be as good.
Yet, there will always be those of us who want to change things. My students aren't as quick as yours. My course isn't anywhere near as long, and I can set less work. I bet you will start to see courses that are somewhat focused, on the life sciences or arts. There will be courses that do require some programming, or mathematics. In that case the ND will be a killer, and make adoption much less likely.
from textbook.
maybe @fperez has thoughts on this as well. Fernando what license are you using for the DS100 textbook?
from textbook.
@choldgraf The DS100 textbook's README says it is licensed under CC BY-NC-ND 4.0.
from textbook.
ah ok - I think that's pretty near the same - my guess is that the problem in question is the "no-derivatives" clause, since many people would want to remix this material for use in their own courses (or if they have shorter-then-a-semester courses)
from textbook.
Ultimately the decision isn't up to me - I'm using the textbook in DS100 but I haven't had any hand in its authorship. I'm just a guy on github here :)
I do think that -ND clauses in content make it more difficult to really reuse the content elsewhere, for reasons including those articulated by Matthew above. The impact of these materials could be even larger if others can more flexibly adapt them.
FWIW, I think it might be viable to come up with a model similar to what Mozilla uses for Firefox: the code is open source but the name is trademarked and has different restrictions - this leads Debian to ship IceWeasel instead - Firefox renamed to comply with the Mozilla conditions. RedHat uses the same thing, which is what makes CentOS basically RedHat minus the names.
If the issue is regarding the protection of the name/brand for Data8/100, then I could imagine licensing the content under say CC-BY-NC or CC-BY but adding a restriction on the name itself (though I don't know if that would require formal trademarking first).
But the authors (Ani and John) may have had a different reason for selecting the name, so I won't speak for them. Happy to discuss it further, here or on campus, obviously.
from textbook.
Ah - that is a shame. Here in the UK, we're thinking about how to expand our data science teaching quickly, and that closes a door to something that would have been a very good foundation.
from textbook.
ah that is too bad - I think that this ND clause drastically limits the impact that the textbook could have (and the "Data 8 @ other institutions" model more generally). However it is you + Ani's call.
from textbook.
from textbook.
@papajohn - I wrote some of the reasons and use-cases in the comment up at #36 (comment) . I'm teaching a course, that I was planning to base on the Berkeley course, and, in practice I've found that it's very difficult to stick so completely to the Data 8 track that it makes sense to point people to individual chapters. I can see, from multiple readings, how carefully you have built up the exposition - with the consequence that taking a chapter here or there simply doesn't work. Honestly I think that would be true for any well-written textbook.
I think you will find that it doesn't really help in reducing the impact of the ND, saying yes on an individual basis, because the remix remains ND, and my impression is that many of us in this space find it uncomfortable writing something that can't easily be re-used.
from textbook.
Related Issues (20)
- Chapter 11 reinforces racist beliefs HOT 4
- Local build error: Landing page missing a title: index HOT 1
- The book will not deploy until it is either updated or the deploy infra is fixed HOT 2
- Delete `gh-pages` branch once we are confident the switch is successful
- Fair use of CC license
- Binder HOT 3
- Invalid Certificate for www.inferentialthinking.com HOT 2
- Name 'read_url' is not defined HOT 2
- Ugly x-axis labels in Chapter 7
- Section 12.3 typo
- Chapter 8.5 typo: 271
- Chapter 11.3.5 typo
- JupyterHub link on each page doesn't work HOT 1
- Binder integrations broken HOT 3
- Chapter 7.1.4 Typo
- Chapter 7.1.3 Typo
- cannot run ch 1 code in colab: Table' object has no attribute 'cumsum' HOT 3
- Minor typos in chapter 13 // open PR #182 HOT 1
- Binder integration not working HOT 4
- Consider alternative frameworks for data structures? HOT 3
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from textbook.