1. Character Trajectories: Multiple, labelled samples of pen tip trajectories recorded whilst writing individual characters. All samples are from the same writer, for the purposes of primitive extraction. Only characters with a single pen-down segment were considered.
2. Human Activity Recognition Using Smartphones: Human Activity Recognition database built from the recordings of 30 subjects performing activities of daily living (ADL) while carrying a waist-mounted smartphone with embedded inertial sensors.
3. Daily and Sports Activities: The dataset comprises motion sensor data of 19 daily and sports activities each performed by 8 subjects in their own style for 5 minutes. Five Xsens MTx units are used on the torso, arms, and legs.
4. Gas Sensor Array Drift Dataset at Different Concentrations: This archive contains 13910 measurements from 16 chemical sensors exposed to 6 different gases at various concentration levels.
5. Activities of Daily Living (ADLs) Recognition Using Binary Sensors: This dataset comprises information regarding the ADLs performed by two users on a daily basis in their
6. Dataset for ADL Recognition with Wrist-worn Accelerometer: Recordings of 16 volunteers performing 14 Activities of Daily Living (ADL) while carrying a single wrist-worn tri-axial accelerometer.
7. ElectricityLoadDiagrams20112014: This data set contains electricity consumption of 370 points/clients.
8. Taxi Service Trajectory - Prediction Challenge, ECML PKDD 2015: An accurate dataset describing trajectories performed by all the 442 taxis running in the city of Porto, in Portugal.
9. UJIIndoorLoc-Mag: The UJIIndoorLoc-Mag is an indoor localization database to test Indoor Positioning System that rely on Earth's magnetic field variations.
10. Educational Process Mining (EPM): A Learning Analytics Data Set: Educational Process Mining data set is built from the recordings of 115 subjects' activities through a logging application while learning with an educational simulator.
11. Heterogeneity Activity Recognition: The Heterogeneity Human Activity Recognition (HHAR) dataset from Smartphones and Smartwatches is a dataset devised to benchmark human activity recognition algorithms (classification, automatic data segmentation, sensor fusion, feature extraction, etc.) in real-world contexts; specifically, the dataset is gathered with a variety of different device models and use-scenarios, in order to reflect sensing heterogeneities to be expected in real deployments.
12. Open University Learning Analytics dataset: Open University Learning Analytics Dataset contains data about courses, students and their interactions with Virtual Learning Environment for seven selected courses and more than 30000 students.
13. Geo-Magnetic field and WLAN dataset for indoor localisation from wristband and smartphone: A multisource and multivariate dataset for indoor localisation methods based on WLAN and Geo-Magnetic ﬁeld ﬁngerprinting
14. FMA: A Dataset For Music Analysis: FMA features 106,574 tracks and includes song title, album, artist, genres; play counts, favorites, comments; description, biography, tags; together with audio (343 days, 917 GiB) and features.
15. BLE RSSI Dataset for Indoor localization and Navigation: This dataset contains RSSI readings gathered from an array of Bluetooth Low Energy (BLE) iBeacons in a real-world and operational indoor environment for localization and navigation purposes.
16. Parking Birmingham: Data collected from car parks in Birmingham that are operated by NCP from
Birmingham City Council. UK Open Government Licence (OGL).
17. 3W dataset: The first realistic and public dataset with rare undesirable real events in oil wells.
18. MEx: The MEx Multi-modal Exercise dataset contains data of 7 different
physiotherapy exercises, performed by 30 subjects recorded with 2 accelerometers,
a pressure mat and a depth camera.
19. Kitsune Network Attack Dataset: A cybersecurity dataset containing nine different network attacks on a commercial IP-based surveillance system and an IoT network. The dataset includes reconnaissance, MitM, DoS, and botnet attacks.
20. selfBACK: The SELFBACK dataset is a Human Activity Recognition Dataset of 9
activity classes recorded with two tri-axial accelerometers.
21. BitcoinHeistRansomwareAddressDataset: BitcoinHeist datasets contains address features on the heterogeneous Bitcoin network to identify ransomware payments.