Reusability-targeted enrichment of sea ice core data.

IF 5.8 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-03-20 DOI:10.1038/s41597-025-04665-x

Anna Simson, Anil Yildiz, Julia Kowalski

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引用次数: 0

Abstract

The Reusability-targeted Enriched Sea Ice Core Database (RESICE) combines data and metadata from 287 sea ice cores. The database enables reuse scenarios such as the validation of physics-based models and the training of data-driven algorithms. RESICE is enriched in two ways. First, RESICE combines data and metadata originating from 138 sources including 107 data sets from the repositories Zenodo, Australian Antarctic Data Center and Pangaea. Second, RESICE contains additional automatically generated metadata tailored to specific reuse scenarios. RESICE is checked for plausibility and consistency, and it allows transparent retracing of each data point to its source. RESICE is accessible via Zenodo and the MOSAiC webODV, and it is extendable through the pyresice Python package. In addition to describing RESICE, we formalize the reuse perspective of an agnostic reuser, uninvolved in data acquisition, and we discuss the process of the cross-source and -repository combination of the database. Despite sources adhering to FAIR, this process is challenging and time-intensive due to the heterogeneity of the sources and their mismatch with reuse requirements.

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.