| | --- |
| | annotations_creators: |
| | - no-annotation |
| | language: |
| | - en |
| | language_creators: |
| | - other |
| | license: |
| | - mit |
| | multilinguality: |
| | - monolingual |
| | pretty_name: LIFD Magnetic Fields |
| | size_categories: [] |
| | source_datasets: [gufm1 model] |
| | tags: [] |
| | task_categories: |
| | - feature-extraction |
| | - image-to-image |
| | - time-series-forecasting |
| | - object-detection |
| | - unconditional-image-generation |
| | task_ids: |
| | - multivariate-time-series-forecasting |
| | --- |
| | |
| | # Dataset Card for LFID Magnetic Field Data |
| |
|
| | You will need the package |
| | https://chaosmagpy.readthedocs.io/en/master/ |
| |
|
| |
|
| | ## Table of Contents |
| | - [Dataset Description](#dataset-description) |
| | - [Dataset Summary](#dataset-summary) |
| | - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| | - [Dataset Structure](#dataset-structure) |
| | - [Data Fields](#data-fields) |
| | - [Dataset Creation](#dataset-creation) |
| | - [Source Data](#source-data) |
| | - [Additional Information](#additional-information) |
| | - [Dataset Curators](#dataset-curators) |
| | - [Licensing Information](#licensing-information) |
| | - [Citation Information](#citation-information) |
| | - [Contributions](#contributions) |
| |
|
| | ## Dataset Description |
| |
|
| | - **Homepage:** [LIFD DataSets homepage](https://cemac.github.io/LIFD_ML_Datasets/) |
| | - **Repository:** [LIFD GitHub Repo](https://github.com/cemac/LIFD_ML_Datasets/) |
| | - **Point of Contact:** [*coming soon*]() |
| |
|
| | ### Dataset Summary |
| |
|
| | A description of the dataset: |
| |
|
| | The gufm1 model is a global geomagnetic model based on spherical harmonics, covering the period 1590 - 1990, and is described in the publication: |
| | [Andrew Jackson, Art R. T. Jonkers and Matthew R. Walker (2000), “Four centuries of geomagnetic secular variation from historical records”, Phil. Trans. R. Soc. A.358957–990, http://doi.org/10.1098/rsta.2000.0569](https://royalsocietypublishing.org/doi/10.1098/rsta.2000.0569) |
| |
|
| |
|
| | ### Supported Tasks and Leaderboards |
| |
|
| |
|
| | ### Data Fields |
| |
|
| | The dataset has dimension (181, 361, 401) whose axes represent co-latitude, longitude, time, and whose values are the radial magnetic field at the core-mantle boundary (radius 3485km) in nT. |
| | The colatitude takes values (in degrees): 0,1,2,3,…180; longitude (degrees) takes values -180,-179,….180; and time is yearly 1590, 1591, …1990. |
| |
|
| |
|
| | ## Dataset Creation |
| |
|
| | The native model representation is converted into a discrete dataset in physical space and time, using the Python package [Chaosmagpy](https://chaosmagpy.readthedocs.io/en/master/) |
| |
|
| | ### Source Data |
| |
|
| | ## Additional Information |
| |
|
| | ### Dataset Curators |
| |
|
| |
|
| | ### Licensing Information |
| | MIT Licence |
| |
|
| |
|
| | ### Citation Information |
| |
|
| |
|
| | ### Contributions |
| |
|
| |
|
