Table 1.

Challenges of international data governance in neuroscience.

Challenge	Description
Ethics	Understanding the ethical imperative for openness on the one hand and the need for data protection compliance on the other; also differences in organizational and cultural values as well as the ethical frameworks and principles underlying the concept of data governance (Fothergill et al., 2019; Salles and Farisco, 2020; Stahl et al., 2018). For example, linking between neural data, cognitive processes, mental states, and mental integrity might have potential benefits but also threats such as manipulation (Yuste et al., 2017) (see also the Neurorights Center at Columbia Universityhttps://nri.ntc.columbia.edu/).
Regulations and Policies	Differences in regulations and policies, including those governing human and animal protections, and different interpretations of regulations and policies. Lack of clarity on regulations and policies overall, and lack of notification of changes to regulations and policies (Rosenbaum, 2010).
Different definitions of Core concepts	Core data concepts such as de-identification, anonymization, and pseudonymization may not mean the same thing in different countries due to varied understanding of personal data (Wiener et al., 2016). Most often anonymization and de-identification are used synonymously in literature. However, anonymization refers to an irreversible process, whereas de-identification gives a room for re-identification which is closer in meaning to pseudonymization than anonymization (Kissner, 219AD; Wiener et al., 2016). Supplementary Figure 1 demonstrates how these are conceptualized and regulated by data protection regulations especially, by the GDPR.
Language	The lack of IDG can create challenges due to differences in language and interpretation between partners. For example, relevant ethical and legal documents that influence data governance are in different languages that the individual researcher may not understand (English, German, French, Japanese, Chinese, Indian, Spanish, Swedish). This highlights one of the problems posed by the increasing internationalization of neuroscience research.
Cultural diversity	In addition to language differences, there are different regional and organizational cultural differences that can affect data sharing. These differences may include social and cultural constructs about the brain and mind, diversity in ethical frameworks and principles, political and regional priorities, as well as approaches to intellectual property management. Sensitivity to these cultural differences is needed for an effective data sharing ecosystem.
Size, complexity and diversity of data	Neuroscience data sets are big and comprise lots of data. In addition to the technical challenges of hosting and harmonizing all of these data, the size and complexity of neuroscience data will likely move the scientific community towards hosting data in accessible environments such as the cloud and bringing computers to the data. There are costs associated with building, and sustaining these infrastructures that may be beyond the reach of researchers in many geographic areas. Should governments develop their own national infrastructure to support big data research or let data be collected outside of government-run infrastructures? If infrastructures are funded by one country, to what extent are they expected to support or subsidize global access to the data hosted by them?