This work was funded through a VIDI grant (452-14-004) provided by the Netherlands Organisation for Scientific Research (NWO), and through the researcher-in-residence program of the Koninklijke Bibliotheek, the national library of the Netherlands. ; Previous studies have highlighted the importance of having long term data for the study of cities, but such sources are relatively scarce. This is especially the case for data about relations between cities, which is a crucial aspect of urban dynamics. Over the last two decades, many efforts have been made to digitalize texts, including books and newspapers, which are primary sources on most of our societies. Researchers have shown that these massive digital archives can be used to identify macroscopic trends related to historical and cultural changes. The wealth of geographic information in such digital archives has not been used much, while they are very valuable for the study of cities. In this paper, we present DIGGER, a newly developed dataset that we built on Delpher, the digital archive of historical newspapers of the National Library of the Netherlands, by extracting geographical information from a selection of 102 million of news items. This dataset allowed us to study the spatial diffusion of information on and between the Dutch cities from a corpus of 81 newspapers published in 29 different cities between 1869 and 1994. This paper presents the method developed to build the dataset as well as the validation steps for the accuracy of the place name recognition. This dataset can be used to study the evolution of the Dutch urban system as well as aspects related to the spatial diffusion of information and geographical bias in media coverage. ; Peer reviewed