In the Open Research – Open Software<\/a> chapters we have explored what open software is, how to implement it in your research and how it can be used. Open Software can be defined differently depending on context<\/a>. Open source does not equal free or Free<\/a>, nor does closed source equal paid, and even Software as a Service<\/a> products may have open source \/ locally runnable versions. Using open formats can help to facilitate long term access to your research for reproducibility, replicability, and reuse. Similarly, well articulated code<\/a>, directly connected to your prose, is fundamental to making your research understandable. Generative AI tools can greatly help in creating understandable code.<\/p>\n Practices like version control<\/a> and containerization<\/a> further strengthen transparency by recording how projects evolve and by making it easier for others to reproduce research environments and results. Large language models may also play a role in analysis, provided repeatability remains a central consideration. There is no single correct open software solution. The most appropriate choice is the one that aligns with your research goals, your comfort with the technology, and the specific needs of your project.<\/p>\n <\/p>\n Free Software (with a capital F) refers to a specific philosophical approach to software that emphasizes the user\u2019s freedom to run, study, modify, and share both the original and modified program.<\/p>\n<\/div>