Attributing and Referencing (Research) Software: Best Practices and Outlook from Inria
This addresses the issue of software attribution for researchers across all fields, but it is incremental as it builds upon existing efforts to develop guidelines.
The paper tackles the problem of inadequate means to cite and reference software in scientific research by proposing three key recommendations, including a richer taxonomy for software contributions, emphasizing human-centric evaluation, and distinguishing citation from reference, based on Inria's internal experience.
Software is a fundamental pillar of modern scientiic research, not only in computer science, but actually across all elds and disciplines. However, there is a lack of adequate means to cite and reference software, for many reasons. An obvious rst reason is software authorship, which can range from a single developer to a whole team, and can even vary in time. The panorama is even more complex than that, because many roles can be involved in software development: software architect, coder, debugger, tester, team manager, and so on. Arguably, the researchers who have invented the key algorithms underlying the software can also claim a part of the authorship. And there are many other reasons that make this issue complex. We provide in this paper a contribution to the ongoing eeorts to develop proper guidelines and recommendations for software citation, building upon the internal experience of Inria, the French research institute for digital sciences. As a central contribution, we make three key recommendations. (1) We propose a richer taxonomy for software contributions with a qualitative scale. (2) We claim that it is essential to put the human at the heart of the evaluation. And (3) we propose to distinguish citation from reference.