10.7910/DVN/V71K5R Abhinav Nippani Abhinav Nippani Northeastern University Dongyue Li Northeastern University Harvard Dataverse 2023 Computer and Information Science Graph Neural Networks, Traffic Accident Analysis, Road Networks Ryan Zhang Ryan Zhang Northeastern University 2023-10-26 2024-02-29 361306677 115139552 130213642 513596407 419971172 1043154295 116918369 963893659 1289728949 1945584912 278418898 application/zip application/zip application/zip application/zip application/zip application/zip application/zip application/zip application/zip application/zip application/zip 2.0 Creative Commons CC0 1.0 Universal Public Domain Dedication. Here we deposit the datasets we have extracted for ten states in the US. 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. 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: (1) adj_matrix.pt: The sparse adjacency matrix of the road network. (2) accidents_monthly.csv: All accidents spanning multiple years and aggregated by month. (3) Nodes/: The node features, including weather information, every month. (4) node_features_{year}_{month}.pt: The weather information of a particular month. (5) Edges/: The edge features, including road and traffic volume information, if available. (6) edge_features.pt: Edge features describing the road information. (7) edge_features_traffic_{year}.pt: Traffic volume records of a particular year.