Various Time Series Anomaly Detection Datasets

该数据集包含了50个广泛应用于时间序列异常检测的知名数据集，这些数据集根据数据生成性质、实体数量、多样性类型、维度数量、样本总数以及应用领域等属性进行了详细特征描述。此外，这些数据集的更新情况也会根据原作者的最新贡献进行报告。该任务的目的是进行时间序列中的异常检测。

This dataset includes 50 well-established datasets widely utilized for time series anomaly detection. Each of these datasets has been thoroughly characterized based on attributes such as data generation properties, number of entities, diversity types, number of dimensions, total sample count, and application domains. Furthermore, updates to these datasets will be documented in accordance with the latest contributions from their original authors. The objective of this task is to perform anomaly detection in time series.