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In each zip file, we include each state's accident records, road networks, and network features. For further information about using the dataset and how we extracted the data, check out our GitHub repository for instructions."},"dsDescriptionDate":{"typeName":"dsDescriptionDate","multiple":false,"typeClass":"primitive","value":"2024-02-29"}}]},{"typeName":"subject","multiple":true,"typeClass":"controlledVocabulary","value":["Computer and Information Science"]},{"typeName":"keyword","multiple":true,"typeClass":"compound","value":[{"keywordValue":{"typeName":"keywordValue","multiple":false,"typeClass":"primitive","value":"Graph Neural Networks, Traffic Accident Analysis, Road Networks"}}]},{"typeName":"notesText","multiple":false,"typeClass":"primitive","value":"For each state, because there are multiple files in the dataset, we uploaded a zip file that includes all the files for that state. As a summary, once you download the zip file, unzip it, then there should be the following files in it:\n\n(1) adj_matrix.pt: The sparse adjacency matrix of the road network.\n\n(2) accidents_monthly.csv: All accidents spanning multiple years and aggregated by month.\n\n(3) Nodes/: The node features, including weather information, every month.\n\n(4) node_features_{year}_{month}.pt: The weather information of a particular month.\n\n(5) Edges/: The edge features, including road and traffic volume information, if available.\n\n(6) edge_features.pt: Edge features describing the road information.\n\n(7) edge_features_traffic_{year}.pt: Traffic volume records of a particular year."}]}},"files":[{"label":"CA-1.zip","restricted":false,"version":1,"datasetVersionId":375301,"dataFile":{"id":8564456,"persistentId":"","filename":"CA-1.zip","contentType":"application/zip","friendlyType":"ZIP 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