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A basic understanding of software licenses and related topics is necessary for RSEs to successfully publish their research software from the legal point of view. Typical questions are: What license should I use for code, documentation, or data? Can I combine this specific set of software licenses? How to document this information? This talk gives an overview about the copyright and software license basics. Using an example of a data analysis script written in Python, we go through the process of clarifying all relevant aspects and documenting them in a practical way. In this context, we introduce REUSE SOFTWARE which provides a standardized approach to document copyright and license information as well as helpful tools.
reuse-software, copyright software-licenses reuse-software rse, copyright, software-licenses, deRSE23, rse
reuse-software, copyright software-licenses reuse-software rse, copyright, software-licenses, deRSE23, rse
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 66 |

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