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PmagPy Online: Jupyter Notebooks, the PmagPy Software Package and the Magnetics Information Consortium (MagIC) Database
  • +4
  • Lisa Tauxe,
  • Rupert Minnet,
  • Nick Jarboe,
  • Catherine Constable,
  • Anthony Koppers,
  • Lori Jonestrask,
  • Nick Swanson-Hysell
Lisa Tauxe
Scripps Institution of Oceanography

Corresponding Author:ltauxe@ucsd.edu

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Rupert Minnet
Oregon State University
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Nick Jarboe
Scripps Institution of Oceanography
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Catherine Constable
Scripps Institution of Oceanography
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Anthony Koppers
Oregon State University
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Lori Jonestrask
Scripps Institution of Oceanography
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Nick Swanson-Hysell
University of California, Berkely
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Abstract

The Magnetics Information Consortium (MagIC), hosted at http://earthref.org/MagIC is a database that serves as a Findable, Accessible, Interoperable, Reusable (FAIR) archive for paleomagnetic and rock magnetic data. It has a flexible, comprehensive data model that can accomodate most kinds of paleomagnetic data. The **PmagPy** software package is a cross-platform and open-source set of tools written in Python for the analysis of paleomagnetic data that serves as one interface to MagIC, accommodating various levels of user expertise. It is available through github.com/PmagPy. Because PmagPy requires installation of Python, several non-standard Python modules, and the PmagPy software package, there is a speed bump for many practitioners on beginning to use the software. In order to make the software and MagIC more accessible to the broad spectrum of scientists interested in paleo and rock magnetism, we have prepared a set of Jupyter notebooks, hosted on [jupyterhub.earthref.org](https://jupyterhub.earthref.org) which serve a set of purposes. 1) There is a complete course in Python for Earth Scientists, 2) a set of notebooks that introduce PmagPy (pulling the software package from the github repository) and illustrate how it can be used to create data products and figures for typical papers, and 3) show how to prepare data from the laboratory to upload into the MagIC database. The latter will satisfy expectations from NSF for data archiving and for example the AGU publication data archiving requirements.