As scientific research and innovation increasingly leave a digital “footprint”, datasets are
becoming ever larger, more complex and available at higher speed. At the same time,
technological advances–in machine learning (ML) and natural language processing, for
example–are opening new analytical possibilities. Science, technology and innovation (STI)
policy can benefit from these dynamics (Box 7.1). They can harness the power of
digitalisation to link and analyse datasets covering diverse areas of policy activity and …

Digitalisation will profoundly affect the public sector and the evidence base on which it
formulates, implements, monitors and evaluates public policy. The science, technology and
innovation (STI) policy field is no exception. In recent years, many countries have begun to
develop digital science and innovation policy (DSIP) initiatives, to help build a picture of the
incidence and impact of their science and innovation activities. This chapter provides an
introductory overview of DSIP systems in OECD member and partner countries. Drawing on …