While availability of research data is widely accepted as undisputable for transparent and reproducible research, research software is not yet recognized and supported as equally important component of scientific discovery. Not only the scholarly paper along with the data behind the findings, but also the associated software should be published in a findable, accessible, interoperable, and reusable (FAIR) manner. However, different measures are required for the data and the software, and satisfying the FAIR principles for software is not (yet) a quality standard in research. Moreover, dedicated research software competencies are necessary, which create current needs in these interdependent competence fields: the handling of research data and software as well as their archival and publication. To discuss this topic, a workshop was held with different experts in the areas of data science, computer science, data literacy, and didactics. A short overview of the workshop, its findings, and future work will be presented to disseminate the results with the community and involve additional interested people in this process.