AutoGeoFAIR: A framework for evaluating the sharing degree of open earth surface system data based on extended FAIR principles

Abstract

Expert participation and collaboration are an efficient, transparent, credible and innovative way to implement open scientific data management, evaluation and analytical mining. An unprecedented surge in openly accessible earth surface system (ESS) data across web platforms has emerged. This data is characterized by dispersion, multi-sourcing, heterogeneity, and multi-modality, and predominantly manifests through thematic sharing websites, data services, metadata, and journal publications, particularly data papers. Addressing the pressing need to swiftly evaluate the sharing degree of these openly shared ESS data sets constitutes a new frontier in this domain. Current frameworks and tools designed for open scientific data sharing lack direct applicability to the intricacies of earth surface systems, thereby impeding users' access to data of high sharing degree. This study introduces an ESS-oriented evaluation tool tailored to assess the sharing degree of open ESS data. Central to this tool are the components of an evaluation metric system and an evaluation model. Leveraging the principles of FAIR (Findable, Accessible, Interoperable, and Reusable), a comprehensive sharing degree assessment index comprising 19 secondary metrics categorized under 5 primary metrics is formulated. Furthermore, a novel evaluation model for quantifying the sharing degree of open scientific data is proposed, integrating hierarchical analysis and the entropy method. This integration effectively captures the nuanced uncertainties and variability inherent in the data, enhancing the accuracy and reliability of evaluation outcomes. The resulting software tool facilitates rapid and quantitative assessment of open scientific data sharing degree within the ESS domain, thereby enabling the recommendation of highly-shared datasets to researchers and modelers alike.

Keywords: Analytic hierarchy process; Expert participation and collaboration; FAIR principles; Open science data; Sharing degree evaluation.