{"@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", "downloadURL": "https://ndownloader.figshare.com/files/43733880", "format": "zip", "mediaType": "application/zip", "title": "vs_data.zip"}], "identifier": "10.15482/USDA.ADC/1528345", "keyword": ["deep learning", "Vesicular Stomatitis Virus", "machine learning", "data.gov", "ARS"], "license": "https://www.usa.gov/publicdomain/label/1.0/", "modified": "2025-11-21", "programCode": ["005:040"], "publisher": {"@type": "org:Organization", "name": "Agricultural Research Service"}, "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"}