This is the accepted (peer-reviewed) version of the following article: Abraham S, Mäs S, Bernard L. Extraction of spatio-temporal data about historical events from text documents. Transactions in GIS. 2018; 22: 677–696. , which has been published in final form at https://doi.org/10.1111/tgis.12448. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited. Extraction of Spatio-Temporal Data about Historical Events from Text Documents Susanna Abraham; Stephan Mäs and Lars Bernard Abstract: Often, we are faced with questions regarding past events and the answers are hidden in the historical text archives. The growing developments in Geographic Information Retrieval and Temporal Information Retrieval techniques have given new ways to explore digital text archives for spatio-temporal data. The question is how to retrieve the answers from the text documents. This work contributes to a better understanding of spatio-temporal information extraction from text documents. Natural Language Processing techniques were used to develop an information extraction approach using the GATE language processing software. The developed framework uses gazetteer matching, spatiotemporal relationship extraction and pattern based rules to recognize and annotate elements in historical text documents. The extracted spatio-temporal data is used as input for GIS studies on the time-geography context of the German-Herero war of resistance 1904 in Namibia. Related issues when analyzing the historical data in current GIS are discussed. Problematic are in particular movement data that is small scale with poor temporal density and trajectories that are short or connect very distant locations. Keywords: spatio-temporal event extraction, natural language processing, historical visualization, geographic information retrieval