Enriched metadata for hybrid data compilations with applications to cryosphere research
In geodisciplines such as the cryosphere sciences, a large variety of data is available in data repositories provided on platforms such as Pangaea. In addition, many computational process models exist that capture various physical, geochemical, or biological processes at a wide range of spatial and...
| Main Authors: | , , |
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| Format: | Conference Object |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://zenodo.org/record/7185423 https://doi.org/10.5281/zenodo.7185423 |
| Summary: | In geodisciplines such as the cryosphere sciences, a large variety of data is available in data repositories provided on platforms such as Pangaea. In addition, many computational process models exist that capture various physical, geochemical, or biological processes at a wide range of spatial and temporal scales and provide corresponding simulation data. A natural thought is to hybridize measured and simulated data into comprehensive data sets that complement each other and provide a joint basis for subsequent model-based interpretation. Two aspects remain challenging, namely a) we are lacking a unified metadata approach that is ready to use for hybrid data compilations comprising both measured and simulated data each with their own characteristics and natural limitations, and b) we are not providing these data compilations in an ‘analysis-ready’ format, for instance, including uncertainties. In this contribution, we present an example from cryosphere science, where much potential remains in a joint interpretation of several field tests and simulation studies to generate an integrated, holistic representation of the ice body. Yet, to date, this joint interpretation is often not feasible because metadata of the measurements lack cross-repository consistency and completeness, and simulated data are often not equipped with metadata at all. We discuss these challenges in light of FAIR, while focusing on the example of sea ice core data. Specifically, we introduce our in-house Ice Data Hub (IDH) as a flexible data management tool that aims to overcome these challenges. We use the IDH to a) store measurement data sets together with enriched, consistent metadata, b) display, add, and plot data sets through its web browser-based GUI, and c) directly couple simulation environments to facilitate interdisciplinary dataflow and interoperability. Lastly, we present an example of an ‘analysis-ready’ sea ice core data set that is merged from individual ice cores stored in the IDH. |
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