HistoGlobe - Teaching History Visually

Kossatz, Marcus; Utzig, Sebastian; Schneegans, Simon; Lauer, Felix; Westphal, T.; Geelhaar, Jens; Froehlich, Bernd; Riehmann, Patrick

doi:10.5220/0006103102010208

Cited by 1 publication

(1 citation statement)

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“…The results demonstrate that automatic extraction of spatio‐temporal information about historical events can provide a structured data basis that can, for example, be used for interactive visual history teaching systems. Such systems can significantly improve the knowledge transfer and understanding of historical processes, beside being much more engaging than traditional methods (Kossatz et al, ).…”

Section: Discussionmentioning

confidence: 99%

Extraction of spatio‐temporal data about historical events from text documents

Abraham

Mäs

Bernard

2018

Transactions in GIS

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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, spatio-temporal relationship extraction and pattern-based rules to recognize and annotate elements in historical text documents. The extracted spatiotemporal data is used as input for GIS studies on the time-geography context of the German-Herero resistance war of 1904 in Namibia. Related issues when analyzing the historical data in current GIS are discussed. Particularly problematic are movement data in small scale with poor temporal density and trajectories that are short or connect very distant locations.

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Section: Discussionmentioning

confidence: 99%