Capturing and sharing our collective expertise on climate data: the CHARMe project

Clifford, D., Alegre, R., Bennett, V., Blower, J., DeLuca, C., Kershaw, P., Lynnes, C., Mattmann, C., Phipps, R. and Rozum, I. (2016) Capturing and sharing our collective expertise on climate data: the CHARMe project. Bulletin of the American Meteorological Society, 97 (4). pp. 531-539. ISSN 1520-0477 doi: 10.1175/BAMS-D-14-00189.1

Abstract/Summary

For users of climate services, the ability to quickly determine the datasets that best fit one's needs would be invaluable. The volume, variety and complexity of climate data makes this judgment difficult. The ambition of CHARMe ("Characterization of metadata to enable high-quality climate services") is to give a wider interdisciplinary community access to a range of supporting information, such as journal articles, technical reports or feedback on previous applications of the data. The capture and discovery of this "commentary" information, often created by data users rather than data providers, and currently not linked to the data themselves, has not been significantly addressed previously. CHARMe applies the principles of Linked Data and open web standards to associate, record, search and publish user-derived annotations in a way that can be read both by users and automated systems. Tools have been developed within the CHARMe project that enable annotation capability for data delivery systems already in wide use for discovering climate data. In addition, the project has developed advanced tools for exploring data and commentary in innovative ways, including an interactive data explorer and comparator ("CHARMe Maps") and a tool for correlating climate time series with external "significant events" (e.g. instrument failures or large volcanic eruptions) that affect the data quality. Although the project focuses on climate science, the concepts are general and could be applied to other fields. All CHARMe system software is open-source, released under a liberal licence, permitting future projects to re-use the source code as they wish.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/44485
Item Type	Article
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Environmental Systems Science Centre Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	American Meteorological Society
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