Another strategy is to contact the authors directly and ask them if they would consider relicensing their work. Many people do not really consider the implications of choosing one license over another and just go with a default.
On Sunday, March 23, 2014 8:59:58 PM UTC-4, John Myles White wrote: > > Yes, including the same GPL-3 license is sufficient if you’ve derived your > work from a GPL-3 project. You may also need to include the original > headers of the files if they contain attribution information that you are > required to preserve. > > I don’t think there’s anything dishonest about creating a GPL-3 package. > If you would like to release something under a permissive license, you’ll > have to implement your code from scratch without ever reading any of the > code from a GPL or closed-source implementation. > > What’s most beneficial depends on context. Many businesses prohibit GPL > software, so many people in the Julia (and Python) communities > intentionally produce MIT or BSD software. But Julia benefits a lot from > having GPL packages when there’s no reasonable alternative. > > — John > > On Mar 23, 2014, at 1:17 PM, Ted Fujimoto <tftu...@gmail.com <javascript:>> > wrote: > > Hi all, > > I'm trying to familiarize myself with Julia by seeing how it compares to > other languages. I would also like to "open-source" my code if it seems > useful to others. Unfortunately, licenses have made this process > complicated. > > A tangible example: > > I am trying to implement a Julia version of the R package pcalg ( > http://cran.r-project.org/web/packages/pcalg/index.html). Like most R > packages, it is protected under the > GPL-3<http://cran.r-project.org/web/licenses/GPL-3> license. > Also, the license states that it would consider my implementation a > "modification" of the R package. Say I feel that my project is ready to be > open-sourced and put it in a github repository. Is it enough to follow the > RmathDist.jl <https://github.com/JuliaStats/RmathDist.jl> lead and do the > following?: > 1. Include the same license in the repository. > 2. Cite the R package I modified. > > A more long term question: I'm guessing a better (and more honest) > alternative to the above would be to implement the relevant algorithms by > looking at the pseudocode and applying it in a way that is friendlier to > future improvements using idiomatic Julia (if it exists yet). After that, > open-source it under the MIT license. Would this be a more beneficial > approach than the "Julia version of an R package" approach? > > >
