Neo4j graph database realizes efficient storage performance of oilfield ontology

• DOI: 10.1371/journal.pone.0207595
• Publication Date: 2018-11-16T19:05:59Z
• Authors: Faming Gong; Yuhui Ma; Wenjuan Gong; Xiaoran Li; Chantao Li; Xiangbing Yuan
• Keywords: Search Engine; Biological Ontologies; Databases, Factual; Science; Q; R; 0202 electrical engineering, electronic engineering, information engineering; Medicine; Database Management Systems; Information Storage and Retrieval; Oil and Gas Industry; 02 engineering and technology; Research Article

The integration of oilfield multidisciplinary ontology is increasingly important for the growth Semantic Web. However, current methods encounter performance bottlenecks either in storing data and searching information when processing large amounts data. To overcome these challenges, we propose a domain-ontology process based on Neo4j graph database. In this paper, focus storage retrieval ontology. We have designed mapping rules from files to regulate database, which can greatly reduce required space. A two-tier index architecture, including object triad indexing, used keep loading times low match with different patterns accurate retrieval. Therefore, method architecture. Based our evaluation, save 13.04% space improve efficiency by more than 30 compared relational databases.