Kiesler, NatalieSchiffner, DanielHenning, Peter A.Striewe, MichaelWölfel, Matthias2022-08-232022-08-232022978-3-88579-716-6https://dl.gi.de/handle/20.500.12116/38835In the context of educational technology research, it is common practice that computer scientists and IT specialists provide support in terms of software and infrastructure for data gathering and processing, storage, analysis and many other services. Ever since Big Data, Learning Analytics and machine learning algorithms have become increasingly feasible, the implementation of programs can be considered a cornerstone of today’s professional research. Contrary to this trend, software as a method for research is hardly recognized within the community, conferences and publication organs. The same applies to processed research data. Therefore, the authors question the current practices and lack of FAIRness related to the publication of software artifacts by discussing the challenges in terms of acknowledgements, review processes, reproducibility and reuse. The paper concludes with recommendations for future FAIR and Open Science practices.enOpen ScienceFAIR principlesepistemologytechnology-based researchsoftwareresearch data managementText/Conference Paper10.18420/delfi2022-0341617-5468