Data Localisation Measures and Their Impacts on Data Science

Nurullaev R., Ursic H., Cuevas M. O., Szulewski P.

In this chapter, we explore the phenomenon of localisation, paying special attention to its impact on data science. Data science is intimately connected with data reuse, as it desperately needs access to data in order to prosper. Provisions on data localisation challenge the idea of a world where information moves freely across borders and instead create an environment in which data is not easily accessible. Hence, data localisation is an issue of great concern as we consider the future of data science.

In the future, the importance of data for these sectors is likely to increase, and the significance of the barriers created by data localisation, if that trend continues, will do so as well. To prevent undesirable consequences of data localisation laws, we propose a set of principles that regulators should refer to in order to avoid unjustified limitations on data transfers and usage, and to allow data science to thrive. Keeping in mind these key guidelines, it is possible to envision a regulation of data flows which is both data science-friendly and protective of individual rights.

Keywords: personal data, data localisation

In book

Research Handbook in Data Science and Law

Berlee A., Busch C., Carlson A., Cuevas M. O., Custers B., Daly A., Franceschi A. D., Kaufmann W., Klop A., Kreifels S., Kryla-Cudna K. M., Lafarre A. J., Mak V., Mattioli M., Nurullaev R., Podszun R., Porcedda M. G., Prins C., Ranchordas S., Russo R., Swinnen K. K., Szulewski P., Ursic H., van der Elst C. F., van Ettekoven B. J., Van Geelen T., Wall D., Zencovich V. Z. Edward Elgar Publishing, 2018.