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

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.