Construction of knowledge graph in the field of grassland plants based on ontology database

Keyi Yang; Yang Liu

doi:10.1117/12.2625579

9 December 2021 Construction of knowledge graph in the field of grassland plants based on ontology database

Keyi Yang, Yang Liu

Proceedings Volume 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021); 121290Q (2021) https://doi.org/10.1117/12.2625579
Event: 2021 International Conference on Environmental Remote Sensing and Big Data, 2021, Wuhan, China

Abstract

In recent years, ecological security issues have been complex and diverse, and grassland ecology has also faced problems such as overgrazing, land desertification, and grassland degradation. The protection of grassland ecology is an important issue. As an important biological resource of grassland ecology, grassland plants play an important role in preventing wind and sand fixation and conserving water and soil. Most of the current related researches are concentrated on the ecological function of certain plants or the category of botany. Therefore, this paper analyzes the composition and relationship of grassland plants on the basis of analysis of previous studies, and designs a conceptual framework for grassland plant knowledge graph construction using an ontology-based method; Using a template-based method and DeepDive knowledge extraction tool to extract knowledge from a large amount of grassland plant data, construct a grassland plant knowledge graph. The knowledge graph constructed in this paper covers the conceptual attributes, inter-species relationships and plant functions of grassland plant entities from a macro perspective. It can help protect grassland plant resources and provide basis and services for grassland ecosystem monitoring, protection and management.

Citation Download Citation

Keyi Yang and Yang Liu "Construction of knowledge graph in the field of grassland plants based on ontology database", Proc. SPIE 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021), 121290Q (9 December 2021); https://doi.org/10.1117/12.2625579

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KEYWORDS

Data modeling

Databases

Forestry

Classification systems

Feature extraction

Ecology

Ecosystems

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