1. AI4I 2020 Predictive Maintenance Dataset: The AI4I 2020 Predictive Maintenance Dataset is a synthetic dataset that reflects real predictive maintenance data encountered in industry.
2. Air Quality: Contains the responses of a gas multisensor device deployed on the field in an Italian city. Hourly responses averages are recorded along with gas concentrations references from a certified analyzer.
3. Appliances energy prediction: Experimental data used to create regression models of appliances energy use in a low energy building.
4. Buzz in social media : This data-set contains examples of buzz events from two different social networks: Twitter, and Tom's Hardware, a forum network focusing on new technology with more conservative dynamics.
5. CNNpred: CNN-based stock market prediction using a diverse set of variables: This dataset contains several daily features of S&P 500, NASDAQ Composite, Dow Jones Industrial Average, RUSSELL 2000, and NYSE Composite from 2010 to 2017.
6. 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.
7. Gas sensor array temperature modulation: A chemical detection platform composed of 14 temperature-modulated metal oxide (MOX) gas sensors was exposed during 3 weeks to mixtures of carbon monoxide and humid synthetic air in a gas chamber.
8. Gas sensor array under dynamic gas mixtures: The data set contains the recordings of 16 chemical sensors exposed to two dynamic gas mixtures at varying concentrations. For each mixture, signals were acquired continuously during 12 hours.
9. 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
10. News Popularity in Multiple Social Media Platforms: Large data set of news items and their respective social feedback on multiple platforms: Facebook, Google+ and LinkedIn.
11. Pedestrian in Traffic Dataset: This data-set contains a number of pedestrian tracks recorded from a vehicle driving in a town in southern Germany. The data is particularly well-suited for multi-agent motion prediction tasks.
12. PPG-DaLiA: PPG-DaLiA contains data from 15 subjects wearing physiological and motion sensors, providing a PPG dataset for motion compensation and heart rate estimation in Daily Life Activities.
13. SML2010: This dataset is collected from a monitor system mounted in a domotic house. It corresponds to approximately 40 days of monitoring data.
14. UJIIndoorLoc-Mag: The UJIIndoorLoc-Mag is an indoor localization database to test Indoor Positioning System that rely on Earth's magnetic field variations.
15. WESAD (Wearable Stress and Affect Detection): WESAD (Wearable Stress and Affect Detection) contains data of 15 subjects during a stress-affect lab study, while wearing physiological and motion sensors.