Recent developments in empirical research within the past decade have shown a greater interest in sources of data. Two different directions are observed. On the one hand, deeper granularity is becoming more important. This covers providing statistical information and indicator values beyond NUTS 2 level aiming at using geo-coded statistical data. On the other hand, new data sources, often called big data, are of growing interest to researchers. Both fields urge the need for (further) developing adequate statistical models to draw inference. Additionally, the type and amount of data yields new challenges such as algorithmic problems due to the complexity as well as confidentiality problems. The latter often causes restrictions for data access and, hence, hampers independent research. The Covid pandemic has shown how important data access is nowadays to enable quick, reliable, and independent research in order to support evidence-based policy.
