A Smart Data Hub to integrate subsurface properties into model-based decision-support tools
Scientific Data, vol. 13
Abstract
The selection of suitable nuclear waste disposal sites is a long and challenging process, involving multiple technical and environmental assessments. For data-integrated simulation models to function as credible decision-support tools in this sensitive context, their data sources must meet rigorous transparency and reproducibility standards. This paper introduces a Smart Data Hub that provides the reproducible data foundation required to address the limits found in existing research, which rarely features both a dataset containing uncertainty information and an effective way of application for specific use cases. The Smart Data Hub is an integrated solution consisting of two main components: a dataset compiled from 50 literature sources covering geological information, structural data, and rock properties for potential repository sites in Germany, and a functional module supporting effective assembly of data compilations for a given geological structure. This approach provides reliable, reproducible data compilation for model-based decision support in the site selection process by providing transparent, uncertainty-informed data coupled with intelligent assembly capabilities.
Authors 4
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Affiliation as printed
Methods for Model-based Development in Computational Engineering, RWTH Aachen University, Aachen, Germany. chen@mbd.rwth-aachen.de
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Affiliation as printed
Geophysical Imaging and Monitoring, RWTH Aachen University, Aachen, Germany
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Affiliation as printed
Geophysical Imaging and Monitoring, RWTH Aachen University, Aachen, Germany
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Julia Kowalski corresponding Aachen Methods for Model–based Development in Computational Engineering
Affiliation as printed
Methods for Model-based Development in Computational Engineering, RWTH Aachen University, Aachen, Germany. kowalski@mbd.rwth-aachen.de
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