Enhancing the FAIRness of Arctic Research Data Through Semantic Annotation

• DOI: 10.5334/dsj-2024-002
• Publication Date: 2024-01-17T11:05:07Z
• Authors: Steven S. Chong; Mark Schildhauer; Margaret O’Brien; Bryce Mecum; Matthew B. Jones
• Keywords: 0106 biological sciences; Science (General); fair; data repository; 01 natural sciences; semantic annotation; arctic research data; Q1-390; data discovery; knowledge modeling; Arctic research data; FAIR

The National Science Foundation's Arctic Data Center is the primary data repository for NSF-funded research conducted in Arctic.There are major challenges discovering and interpreting resources a containing as heterogeneous interdisciplinary those Center.This paper reports on advances cyberinfrastructure at that help address these issues by leveraging semantic technologies enhance repository's adherence to FAIR principles improve Findability, Accessibility, Interoperability, Reusability of digital repository.We describe Center's improvements.We use annotation bind metadata about sets with concepts web-accessible ontologies.The implementation mechanism accompanied development an extended search interface increases findability allowing users specific, broader, narrower meanings measurement descriptions, well through their potential synonyms.Based carried out DataONE project, we evaluated impact this approach, regarding accessibility, interoperability, reusability data.Arctic often benefits from having additional data, typically multiple, sources, complement extend bases -spatially, temporally, or thematically -for understanding phenomena.These relevant must be 'found', 'harmonized' prior integration analysis.The findings case study indicated enhances capabilities researchers accomplish tasks.