Data linkage is the task of matching and aggregating records that relate to the same entity from one or more data sets. A related technique is geocoding, the matching of ad- dresses to their geographic locations. As data linkage is often based on personal information (like names and ad- dresses), privacy and confidentiality are of paramount im- portance. In this paper we present an overview of current approaches to privacy-preserving data linkage, and dis- cuss their limitations. Using real-world scenarios we illus- trate the significance of developing improved techniques for automated, large scale and distributed privacy-preserving linking and geocoding. We then discuss four core research areas that need to be addressed in order to make linking and geocoding of large confidential data collections feasible.