
Software plays a crucial role in academic research, not only as a tool for data analysis but also as a research outcome or result, or even the object of research itself. FAIR (Findable, Accessible, Interoperable, Reusable) research software can increase the transparency, reproducibility, and reusability of research. For this to happen, software needs to be well-described (by metadata), inspectable, documented and appropriately structured so that it can be executed, replicated, built-upon, combined, reinterpreted, reimplemented, and/or used in different settings. The FAIR4RS Principles aim to guide software creators and owners on how to make their software FAIR. FAIR-IMPACT offered two support actions designed to enhance the FAIRness and impact of research software: Assessing and improving existing research software using a new extension of F-UJI which implements some of the metrics for automated FAIR research software assessment. Implementing the Research Software MetaData (RSMD) guidelines for better archiving, referencing, describing, and citing research software artefacts. This FAIR Implementation Story outlines the specific aims and actions of the Brno University of Technology in relation to their participation in the first (F-UJI) support action. "You should always think of FAIR-RS metrics from the beginning to the end of the computational research tool development process. While you can always address them retrospectively, you will unnecessarily lose potential users of your software." Supported applicant: Karel Sedlář, Jana Musilová, Brno University of Technology
| 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 |
