Model Atlas of the Earth (M@TE): advancing the findability, accessibility, interoperability, and reusability of digital twins

The field of numerical modeling of Earth s systems is playing an instrumental role in understanding mineral resources and geo-hazards. Such models often require specialized computational resources (HPC), can take days-to-weeks to run, and produce large volumes of heterogeneous output data. The lack of curation of these numerical models and community standards hinders our ability to access, interpret and build on published numerical models. Here, we present a first-of-its-kind open science framework that aims to establish a community practice to increase the usefulness of numerical modeling outputs and leverage computational resources. M@TE provides a digital platform that encapsulates the entire model development process: from setup, to model output, and analysis. This supports discovery, data preservation, reproducibility, and reuse, with flexibility for users with different levels of expertise. M@TE has a human-browsable, machine-searchable, user-friendly front end (https://mate.science/ ), and a back-end GitHub organization (https://github.com/ModelAtlasofTheEarth) and model output repository targeted to expert users. Contributions to M@TE are handled by GitHub automation workflows that guide contributors through the process of documenting their models, ensuring that they meet community standards, validating metadata and creating DOIs. M@TE provides a platform for a much wider appreciation of Earth processes and numerical modeling, particularly to industry stakeholders, professional geoscientists and educators. Furthermore, M@te is creating a single platform that will advance the interoperability of digital twins required to address the current environmental crisis.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-30
DOI
https://doi.org/10.5281/zenodo.15293526
Primary Topic
Statistical Methods and Bayesian Inference
Type
article
Field-Weighted Citation Impact
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article

Model Atlas of the Earth (M@TE): advancing the findability, accessibility, interoperability, and reusability of digital twins

Zenodo (CERN European Organization for Nuclear Research)
Statistical Methods and Bayesian Inference
article

Model Atlas of the Earth (M@TE): advancing the findability, accessibility, interoperability, and reusability of digital twins

article en

Abstract

The field of numerical modeling of Earth s systems is playing an instrumental role in understanding mineral resources and geo-hazards. Such models often require specialized computational resources (HPC), can take days-to-weeks to run, and produce large volumes of heterogeneous output data. The lack of curation of these numerical models and community standards hinders our ability to access, interpret and build on published numerical models. Here, we present a first-of-its-kind open science framework that aims to establish a community practice to increase the usefulness of numerical modeling outputs and leverage computational resources. M@TE provides a digital platform that encapsulates the entire model development process: from setup, to model output, and analysis. This supports discovery, data preservation, reproducibility, and reuse, with flexibility for users with different levels of expertise. M@TE has a human-browsable, machine-searchable, user-friendly front end (https://mate.science/ ), and a back-end GitHub organization (https://github.com/ModelAtlasofTheEarth) and model output repository targeted to expert users. Contributions to M@TE are handled by GitHub automation workflows that guide contributors through the process of documenting their models, ensuring that they meet community standards, validating metadata and creating DOIs. M@TE provides a platform for a much wider appreciation of Earth processes and numerical modeling, particularly to industry stakeholders, professional geoscientists and educators. Furthermore, M@te is creating a single platform that will advance the interoperability of digital twins required to address the current environmental crisis.

Zenodo (CERN European Organization for Nuclear Research)
The University of Melbourne (AU)
Openalex Percentile: Top 54%
Statistical Methods and Bayesian Inference
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Model Atlas of the Earth (M@TE): advancing the findability, accessibility, interoperability, and reusability of digital twins · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS