Semantic Publication of Agricultural Scientific Literature Using Property Graphs

Francisco Abad-Navarro, José Antonio Bernabé-Diaz, Alexander García-Castro, Jesualdo Tomás Fernandez-Breis
2020 Applied Sciences  
During the last decades, there has been significant changes in science that have provoked a big increase in the number of articles published every year. This increment implies a new difficulty for scientists, who have to do an extra effort for selecting literature relevant for their activity. In this work, we present a pipeline for the generation of scientific literature knowledge graphs in the agriculture domain. The pipeline combines Semantic Web and natural language processing technologies,
more » ... hich make data understandable by computer agents, empowering the development of final user applications for literature searches. This workflow consists of (1) RDF generation, including metadata and contents; (2) semantic annotation of the content; and (3) property graph population by adding domain knowledge from ontologies, in addition to the previously generated RDF data describing the articles. This pipeline was applied to a set of 127 agriculture articles, generating a knowledge graph implemented in Neo4j, publicly available on Docker. The potential of our model is illustrated through a series of queries and use cases, which not only include queries about authors or references but also deal with article similarity or clustering based on semantic annotation, which is facilitated by the inclusion of domain ontologies in the graph.
doi:10.3390/app10030861 fatcat:4ph46nkc5be3vl5z7kp4oe4xuy