Data from: Modeling the Spread of a Livestock Disease With Semi-Supervised Spatiotemporal Deep Neural Networks
This dataset contains the spatiotemporal data used to train the spatiotemporal deep neural networks described in "Modeling the Spread of a Livestock Disease With Semi-Supervised Spatiotemporal Deep Neural Networks". The dataset consists of two sets of NumPy arrays. The first set: X_grid.npy and Y_grid.npy were used to train the convolutional LSTM, while the second set: X_graph.npy, Y_graph.npy, and edge_index.npy were used to train the graph convolutional LSTM. The data consists of spatiotemporally varying environmental and anthropogenic variables along with case reports of vesicular stomatitis. Resources in this dataset:Resource Title: NumPy Arrays of Spatiotemporal Features and VS Cases. File Name: vs_data.zipResource Description: This is a ZIP archive containing five NumPy arrays of spatiotemporal features and geotagged VS cases.Resource Software Recommended: NumPy,url: https://numpy.org/
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"005:18"
]
|
| contactPoint |
{
"fn": "Stucky, Brian",
"hasEmail": "mailto:brian.stucky@usda.gov"
}
|
| description | <p>This dataset contains the spatiotemporal data used to train the spatiotemporal deep neural networks described in "Modeling the Spread of a Livestock Disease With Semi-Supervised Spatiotemporal Deep Neural Networks". The dataset consists of two sets of NumPy arrays. The first set: <code>X_grid.npy</code> and <code>Y_grid.npy</code> were used to train the convolutional LSTM, while the second set: <code>X_graph.npy</code>, <code>Y_graph.npy</code>, and <code>edge_index.npy</code> were used to train the graph convolutional LSTM. The data consists of spatiotemporally varying environmental and anthropogenic variables along with case reports of vesicular stomatitis. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: NumPy Arrays of Spatiotemporal Features and VS Cases.</p> <p>File Name: vs_data.zip</p><p>Resource Description: This is a ZIP archive containing five NumPy arrays of spatiotemporal features and geotagged VS cases.</p><p>Resource Software Recommended: NumPy,url: <a href="https://numpy.org/">https://numpy.org/</a> </p></li></ul><p></p> |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "vs_data.zip",
"format": "zip",
"mediaType": "application/zip",
"downloadURL": "https://ndownloader.figshare.com/files/43733880"
}
]
|
| identifier | 10.15482/USDA.ADC/1528345 |
| keyword |
[
"ARS",
"Vesicular Stomatitis Virus",
"data.gov",
"deep learning",
"machine learning"
]
|
| license | https://www.usa.gov/publicdomain/label/1.0/ |
| modified | 2025-11-21 |
| programCode |
[
"005:040"
]
|
| publisher |
{
"name": "Agricultural Research Service",
"@type": "org:Organization"
}
|
| spatial |
"{"type": "Polygon", "coordinates": [[[-115.751953125, 31.208103321325], [-111.6650390625, 48.460173285246], [-94.6142578125, 42.877976842874], [-89.9560546875, 36.600094165941], [-99.0966796875, 16.638823475728], [-115.751953125, 31.208103321325]]]}"
|
| temporal | 2001-01-01/2021-01-01 |
| title | Data from: Modeling the Spread of a Livestock Disease With Semi-Supervised Spatiotemporal Deep Neural Networks |
