Constructing Knowledge Graphs for New Species in the Greater Mekong Subregion

<p>Purpose: This study presents a methodology for developing a knowledge graph by integrating World Wildlife Fund (WWF) species discovery reports in the Greater Mekong Subregion. Design/methodology/approach: The research employs a four-phase approach: constructing a taxonomic data model, implementing a graph database, developing a web application architecture, and creating an interactive user interface. Findings: The knowledge graph integrates 2,783 species across 27 taxonomic groups, comprising 12,089 nodes and 30,303 connections. The system enables complex queries through SPARQL endpoints, revealing patterns in species distribution and conservation status from 1997 to 2022. Research limitations: Primary limitations include geographical constraints to the Greater Mekong Subregion and limited integration with external biodiversity databases. Practical implications: The system provides researchers with a graph search engine for exploring species data, supporting scientific research and conservation planning. Originality/value: This study presents a novel approach to organizing biodiversity data by combining taxonomic hierarchies with conservation metrics, establishing a framework for integrating species discovery data.</p>