Bringing Semantics to Support Ocean FAIR Data Services with Ontologies

Abstract

With the increasing attention to ocean and the development of data-intensive sciences, a large amount of ocean data has been acquired by various observing platforms and sensors, which poses new challenges to data management and utilization. Typically, nowadays we target to move ocean data management toward the FAIR principles of being findable, accessible, interoperable, and reusable. However, the data produced and managed by different organizations with wide diversity, various structures and increasing volume make it hard to be FAIR, and one of the most critical reason is the lack of unified data representation and publication methods. In this paper, we propose novel techniques to try to solve the problem by introducing semantics with ontologies. Specifically, we first propose a unified semantic model named OEDO to represent ocean data by defining the concepts of ocean observing field, specifying the relations between the concepts, and describing the properties with ocean metadata. Then, we further optimize the state-of-the-art quick service query list (QSQL) data structure, by extending the domain concepts with WordNet to improve data discovery. Moreover, based on the OEDO model and the optimized QSQL, we propose an ocean data service publishing method called DOLP to improve data discovery and data access. Finally, we conduct extensive experiments to demonstrate the effectiveness and efficiency of our proposals.