A Conceptualization of Research Data in the Context of Industry-Academia Collaborations

Vast knowledge generated in industry and academia is based on the analysis of data. Therefore, access
to 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 data
researchers in industry and academia require is a major obstacle in sharing this data to allow for even
more insights. As various conceptualizations of research data exist, implications for whether and when
data can be considered as “research data” in the context of industry-academia collaborations are fuzzy
and unclear. Therefore, this whitepaper discusses existing academic, industry, and corporate
perspectives on what the concept of research data in the context of industry-academia collaboration
encompasses.

We show that, theoretically, any type of data can become research data. However, in practice, several
factors can affect the usability, relevance, and value of data for research. These factors include legal
obstacles, disciplinary differences in research relevance of data, and insufficient data quality that can
reduce the usability and relevance of data for research, ultimately hindering the possibility of turning
data from industry-academia collaborations into research data. We show that several services provided
by the NFDI and its Section Industry Engagement, data governance best practices, recent generative AI
developments, and currently developed data spaces exist to foster the sharing of relevant research
data between industry and academia.