MagNEO D7.2: Data Management Plan

This deliverable is a report that presents the Data Management Plan (DMP) of the MagNEO project. Its purpose is to establish the main elements of the data management policy of the project that will be used by all project partners with regard to the datasets that will be generated during project implementation. While SINTEF will oversee the implementation of policy, the application of this document is the responsibility of all MagNEO project partners. The DMP of the MagNEO project is a living document which will be updated regularly during the execution of the project and will be reported to the Funding Agency at least halfway through the project and at the end of the project.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-31
DOI
https://doi.org/10.5281/zenodo.14711280
Primary Topic
Computational Physics and Python Applications
Type
article
Field-Weighted Citation Impact
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article

MagNEO D7.2: Data Management Plan

Zenodo (CERN European Organization for Nuclear Research)
Computational Physics and Python Applications
article

MagNEO D7.2: Data Management Plan

article en

Abstract

This deliverable is a report that presents the Data Management Plan (DMP) of the MagNEO project. Its purpose is to establish the main elements of the data management policy of the project that will be used by all project partners with regard to the datasets that will be generated during project implementation. While SINTEF will oversee the implementation of policy, the application of this document is the responsibility of all MagNEO project partners. The DMP of the MagNEO project is a living document which will be updated regularly during the execution of the project and will be reported to the Funding Agency at least halfway through the project and at the end of the project.

Zenodo (CERN European Organization for Nuclear Research)
SINTEF (NO), RTD Talos (Cyprus) (CY), SINTEF Industry (NO)
Industry, innovation and infrastructure
Openalex Percentile: Top 65%
Computational Physics and Python Applications
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