Research Data: A Public Good or a Private Asset? - Nogueira, Tadeu Fernando; Eikebrokk, Trude; Økdal Aksetøy, Laila (Septentrio Conference Series, 2024)
This article is concerned with the issue of how Research Performing Organizations (RPOs) can balance the market and non-market value of the research data they hold. Research data is often viewed as a public good as it is produced at least partly through public funds. As such, research data is expected to be made publicly available and in service of public interests. At the same time, research data has market value and can be viewed as a private asset. This is so because research data is a versatile resource that can be re-purposed for commercial ends. Research data can be an input upon which products or services are built, especially in light of emerging technologies that can automate the compilation and analysis of data with ease (see, for example, Stiglich et al., 2023). The discussion on research data as a public good or a private asset can be contentious. Many hold the view that publicly funded research - including data - should be open to, and for the benefit of, all. At the same time, others argue that there are different ways through which research can achieve its final objective of benefiting society, not least through commercial routes. To address this issue, we adopt Scheiner’s (2020) framework for dealing with opposing perspectives that carry an inherent tension between them. Scheiner proposes four strategies in this regard: (1) to treat the perspectives as lacking a common ground and contradictory, where one perspective is chosen over the other; (2) to treat the perspectives as in constant tension, preserving the paradoxes between them; (3) to treat the perspectives as independent and yet complementary, placing them in dialog with each other; and (4) to treat the perspectives as blending into each other, merging them into a synthesis. Of particular interest to this article are RPOs in the institute sector that operate under both market and non-market logics, which have implications for how they govern their research data. For instance, RPOs in the sector need to comply with mandates on open research data and, at the same time, protect commercially sensitive research data. In the paper, we conceptually apply Scheiner’s framework to RPOs in the institute sector as an illustrative example, in order to gain insights into how these RPOs can move toward an integrated strategy to research data governance. From the discussions undertaken in the article, one of the main conclusions is that these RPOs may benefit from developing a research data governance model that acknowledges both the economic and societal values of research data. See this presentation in this video recording.