Knowledge graph construction and application in geosciences: A review

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Authors

Xiaogang Ma 

Abstract

Knowledge graph (KG) is a topic of great interests to geoscientists as it can be deployed throughout the data life cycle in data-intensive geoscience studies. Nevertheless, comparing with the large amounts of publications on machine learning applications in geosciences, summaries and reviews of geoscience KGs are still limited. The aim of this paper is to present a comprehensive review of KG construction and implementation in geosciences. It consists of four major parts: 1) concepts rele-vant to KG and approaches for KG construction, 2) KG application in data collection, curation, and service, 3) KG application in data analysis, and 4) challenges and trends of geoscience KG creation and application in the near future. For each of the first three parts, a list of concepts, exemplar stud-ies, and best practices are summarized. Those summaries are synthesized together in the challenge and trend analyses. As artificial intelligence and data science are thriving in geosciences, we hope this review of geoscience KGs can be of value to practitioners in data-intensive geoscience studies.

DOI

https://doi.org/10.31223/X5Z898

Subjects

Artificial Intelligence and Robotics, Computer Engineering, Computer Sciences, Databases and Information Systems, Earth Sciences, Environmental Sciences

Keywords

Knowledge graph, Artificial intelligence, Data science

Dates

Published: 2021-04-30 12:17

Last Updated: 2021-04-30 19:17

License

CC BY Attribution 4.0 International

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