| license: apache-2.0 | |
| dataset_info: | |
| features: | |
| - name: id | |
| dtype: int32 | |
| - name: x | |
| dtype: | |
| array2_d: | |
| shape: | |
| - 24 | |
| - 13 | |
| dtype: float32 | |
| - name: station | |
| dtype: | |
| class_label: | |
| names: | |
| '0': Aotizhongxin | |
| '1': Changping | |
| '2': Dingling | |
| '3': Dongsi | |
| '4': Guanyuan | |
| '5': Gucheng | |
| '6': Huairou | |
| '7': Nongzhanguan | |
| '8': Shunyi | |
| '9': Tiantan | |
| '10': Wanliu | |
| '11': Wanshouxigong | |
| - name: year | |
| dtype: | |
| class_label: | |
| names: | |
| '0': '2013' | |
| '1': '2014' | |
| '2': '2015' | |
| '3': '2016' | |
| '4': '2017' | |
| - name: month | |
| dtype: | |
| class_label: | |
| names: | |
| '0': '1' | |
| '1': '2' | |
| '2': '3' | |
| '3': '4' | |
| '4': '5' | |
| '5': '6' | |
| '6': '7' | |
| '7': '8' | |
| '8': '9' | |
| '9': '10' | |
| '10': '11' | |
| '11': '12' | |
| - name: day | |
| dtype: | |
| class_label: | |
| names: | |
| '0': '1' | |
| '1': '2' | |
| '2': '3' | |
| '3': '4' | |
| '4': '5' | |
| '5': '6' | |
| '6': '7' | |
| '7': '8' | |
| '8': '9' | |
| '9': '10' | |
| '10': '11' | |
| '11': '12' | |
| '12': '13' | |
| '13': '14' | |
| '14': '15' | |
| '15': '16' | |
| '16': '17' | |
| '17': '18' | |
| '18': '19' | |
| '19': '20' | |
| '20': '21' | |
| '21': '22' | |
| '22': '23' | |
| '23': '24' | |
| '24': '25' | |
| '25': '26' | |
| '26': '27' | |
| '27': '28' | |
| '28': '29' | |
| '29': '30' | |
| '30': '31' | |
| - name: season | |
| dtype: | |
| class_label: | |
| names: | |
| '0': Summer | |
| '1': Autumn | |
| '2': Winter | |
| '3': Spring | |
| splits: | |
| - name: train | |
| num_bytes: 17082624 | |
| num_examples: 12272 | |
| - name: val | |
| num_bytes: 3660960 | |
| num_examples: 2630 | |
| - name: test | |
| num_bytes: 3660960 | |
| num_examples: 2630 | |
| download_size: 9437882 | |
| dataset_size: 24404544 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: val | |
| path: data/val-* | |
| - split: test | |
| path: data/test-* | |
| ## MSD Beijing Multi-Site Air Quality Dataset Attribution | |
| The Multi-factor Sequential Disentanglement benchmark includes the **Beijing Multi-Site Air Quality (BMS-AQ) dataset**, a time series dataset that captures daily air quality and weather measurements across multiple monitoring stations in Beijing. | |
| For the benchmark, we preprocess this data into daily sequences of 24 hourly records, grouped by station and date. | |
| Each sequence is labeled with static attributes such as station, year, month, day, and season, resulting in a temporal dataset suitable for studying disentanglement in real-world time series. | |
| - Original source: | |
| https://archive.ics.uci.edu/dataset/501/beijing+multi+site+air+quality+data | |
| ``` | |
| @misc{beijing_multi-site_air_quality_501, | |
| author = {Chen, Song}, | |
| title = {{Beijing Multi-Site Air Quality}}, | |
| year = {2017}, | |
| howpublished = {UCI Machine Learning Repository}, | |
| note = {{DOI}: https://doi.org/10.24432/C5RK5G} | |
| } | |
| ``` | |
| ⚠ **Note:** We process and redistribute this dataset solely for non-commercial research purposes. Please cite the above paper when using this dataset in your work. | |