Vast knowledge generated in industry and academia is based on the analysis of data. Therefore, accessto data is fundamental to creating new insights and knowledge. While many public organizations,private companies, and academic institutions possess relevant data, the uncertainty about what dataresearchers in industry and academia require is a major obstacle in sharing this data to allow for evenmore insights. As various conceptualizations of research data exist, implications for whether and whendata can be considered as “research data” in the context of industry-academia collaborations are fuzzyand unclear. Therefore, this whitepaper discusses existing academic, industry, and corporateperspectives on what the concept of research data in the context of industry-academia collaborationencompasses. We show that, theoretically, any type of data can become research data. However, in practice, severalfactors can affect the usability, relevance, and value of data for research. These factors include legalobstacles, disciplinary differences in research relevance of data, and insufficient data quality that canreduce the usability and relevance of data for research, ultimately hindering the possibility of turningdata from industry-academia collaborations into research data. We show that several services providedby the NFDI and its Section Industry Engagement, data governance best practices, recent generative AIdevelopments, and currently developed data spaces exist to foster the sharing of relevant researchdata between industry and academia.