The data hosted here belongs inside the 1_postsim folder, which consists of the following pickle files: normal.pkl, which contains all nominal sequences anomalous.pkl, which contains all anomalous sequences control.pkl, which contains all control-counterparts to anomalous.pkl training.pkl, which contains all pre-determined folds for training training_clean.pkl, a version of training.pkl without anomalous sequences testing.pkl, which contains all pre-determined folds for testing testing_clean.pkl, a version of testing.pkl without anomalous sequences Each pickle file is a list of several 2D NumPy arrays, each representing a multivariate time series. The name of the corresponding .mat file (and, by extension, the label) is present in the metadata. For NumPy object array, it can be read by calling array.dtype.metadata['file_name']. The raw simulation output sequences in the 0_simulation folder are not provided due to the Zenodo file number limit of 100 files. We decided to omit the data belonging to the 2_preprocessed folder as the contents are specific to the TensorFlow data pipeline and the same data host limitations would apply. For more information, refer to the publication (preprint): https://arxiv.org/abs/2411.13951 For access to the source code, refer to the repository on GitHub: https://github.com/lcs-crr/PATHIf you use this dataset for your research, please consider citing it through the menu on the right, or using the following bibtex entry:@misc{correiaDatasetEvaluatingOnline2024a, title = {A {{Dataset}} for {{Evaluating Online Anomaly Detection Approaches}} for {{Discrete Multivariate Time Series}}}, author = {Correia, Lucas and Goos, Jan-Christoph and B{\"a}ck, Thomas and Kononova, Anna V.}, year = {2024}, publisher = {Zenodo}, doi = {10.5281/ZENODO.13255121}, copyright = {MIT License}}