Abstract: In view of the problems such as the low degree of opening and sharing of high-speed railway accidents, data fragmentation, verticalization and fragmentation of information, this paper constructed the ontology layer and data layer of high-speed railway accidents based on the knowledge graph to implement the resource integration of accident data, used the graph database to express the logical relationship of accident causes, generated the fault tree of high-speed railway accident causes through Python programming, and completed the cause analysis of high-speed railway accidents. The analysis results indicate that "illegal operations" and "inadequate supervision" in human factors, as well as "adverse weather" in environmental factors, have led to more high-speed rail accidents. Based on these results, the paper provides practical and feasible suggestions for railway departments to prevent major accidents from occurring.