Dataset Hub

The repository contains scripts for analyzing publicly available log datasets commonly used in anomaly detection (HDFS, BGL, OpenStack, Hadoop, Thunderbird, ADFA, AWSCTD). These datasets are used to evaluate sequence‑based anomaly detection techniques.

This repository offers a suite of real‑world datasets for anomaly detection, covering tabular data (categorical and numerical), time‑series data, graph data, image data, and video data. These datasets support deep anomaly detection research and can be cited alongside the associated publications.

This dataset contains 3,543 chest X‑ray images, annotated with bounding boxes for ten chest abnormalities, including nodules, masses, and pneumothorax. The project uses the ChestX‑Det10 dataset, which is a subset of NIH ChestX‑14.

The ECG‑5000 dataset is an ECG (electrocardiogram) dataset for anomaly detection, containing both normal and abnormal heart signal recordings. It is used to train TCN models to identify anomalous patterns in ECG data.