Earth Science Informatics

, Volume 12, Issue 4, pp 599–613 | Cite as

Ontology-based question understanding with the constraint of Spatio-temporal geological knowledge

  • Wenjia Li
  • Liang WuEmail author
  • Zhong Xie
  • Liufeng Tao
  • Kuanmao Zou
  • Fengdan Li
  • Jinli Miao
Research Article


Spatio-temporal geological big data contain a large amount of spatial and nonspatial data. It is important to effectively manage and retrieve these existing data for geological research, and understanding the question represents the first step. This paper aims to better understand the problem to improve the retrieval efficiency. In geology, the organization of massive unstructured geological data and the discovery of implicit content based on knowledge and relationships have been realized. However, previous findings are primarily based on spatial and nonspatial dimensions, and the key words searched are often just segmented words. In geological research, the dimension of time is as important as spatial and other nonspatial dimensions. In addition, an individual user’s goal may be more than a superficial representation of the problem. In this paper, we first construct the geological event ontology, organize Spatio-temporal big data with this dimension, and expand the concept of geological time. Next, based on geology knowledge, we propose spatio-temporal rules, spatial characteristics, and domain constraint rules to assess the consistency of the ontology and to maximize the relationship between the information and improvements in the efficiency of information retrieval. Then, the ontology question is extended, and the rules between this question and other ontologies are expounded to deepen the understanding of the problem. Finally, we evaluate our contribution over a real geology dataset on a knowledge-driven geologic survey information smart-service platform (GSISSP), which integrates geological thematic ontology, geological temporal ontology, and toponymy ontology. This study reveals a positive impact of the incorporation of multiple ontologies and feature rules, which is meaningful for improving accuracy and comprehensiveness.


Geology Spatio-temporal big-data Ontology Question understanding 



This project was supported by the National Science Foundation of China (Grant No. 41871311, 41671400) and the National Key Research and Development Program (Grant No. 2017YFB0503600, 2017YFC0602204, 2018YFB0505500). The authors thank the Development and Research Center of the China Geological Survey for providing technical support. We thank the National Engineering Research Center of Geographic Information System for providing hardware support.

Author contributions

Conceived and designed the experiments: Wenjia Li, Liang Wu, Zhong Xie, Liufeng Tao, Kuanmao Zou, Fengdan Li and Jinli Miao; Performed the experiments: Wenjia Li, Liang Wu, Zhong Xie, Liufeng Tao, Kuanmao Zou, Fengdan Li and Jinli Miao; Analyzed the data: Wenjia Li, Liang Wu, Zhong Xie, Liufeng Tao, Kuanmao Zou, Fengdan Li and Jinli Miao; Wrote the paper: Wenjia Li, Liang Wu and Zhong Xie.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Wenjia Li
    • 1
  • Liang Wu
    • 1
    • 2
    Email author
  • Zhong Xie
    • 1
    • 2
  • Liufeng Tao
    • 2
  • Kuanmao Zou
    • 1
  • Fengdan Li
    • 3
  • Jinli Miao
    • 3
  1. 1.Faculty of Information EngineeringChina University of GeosciencesWuhanChina
  2. 2.National Engineering Research Center for GISWuhanChina
  3. 3.Development and Research Center, China Geological SurveyBeijingChina

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