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. Behavior of the urban traffic of the city of Sao Paulo in Brazil: The database was created with records of behavior of the urban traffic of the city of Sao Paulo in Brazil. 5. 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. 6. 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. 7. Concrete Slump Test: Concrete is a highly complex material. The slump flow of concrete is not only determined by the water content, but that is also influenced by other concrete ingredients. 8. Condition Based Maintenance of Naval Propulsion Plants: Data have been generated from a sophisticated simulator of a Gas Turbines (GT), mounted on a Frigate characterized by a COmbined Diesel eLectric And Gas (CODLAG) propulsion plant type. 9. CSM (Conventional and Social Media Movies) Dataset 2014 and 2015: 12 features categorized as conventional and social media features. Both conventional features, collected from movies databases on Web as well as social media features(YouTube,Twitter). 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. 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.
12. 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. 13. Gas Turbine CO and NOx Emission Data Set: The dataset contains 36733 instances of 11 sensor measures aggregated over one hour, from a gas turbine located in Turkey for the purpose of studying flue gas emissions, namely CO and NOx. 14. 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 15. GPS Trajectories: The dataset has been feed by Android app called Go!Track. It is available at Goolge Play Store(https://play.google.com/store/apps/details?id=com.go.router). 16. 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. 17. Online Video Characteristics and Transcoding Time Dataset: The dataset contains a million randomly sampled video instances listing 10 fundamental video characteristics along with the YouTube video ID. 18. Optical Interconnection Network : This dataset contains 640 performance measurements from a simulation of 2-Dimensional Multiprocessor Optical Interconnection Network. 19. Paper Reviews: This sentiment analysis data set contains scientific paper reviews from an international conference on computing and informatics. The task is to predict the orientation or the evaluation of a review. 20. 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. 21. 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.
22. Seoul Bike Sharing Demand: The dataset contains count of public bikes rented at each hour in Seoul Bike haring System with the corresponding Weather data and Holidays information 23. SGEMM GPU kernel performance: Running times for multiplying two 2048 x 2048 matrices using a GPU OpenCL SGEMM kernel with varying parameters (using the library 'CLTune'). 24. SML2010: This dataset is collected from a monitor system mounted in a domotic house. It corresponds to approximately 40 days of monitoring data. 25. Steel Industry Energy Consumption Dataset: The data is collected from a smart small-scale steel industry in South Korea. 26. Steel Industry Energy Consumption Dataset: Dataset attributes are lagging and leading current reactive power, the lagging and leading current power factor, carbon dioxide emissions, and load types. Timespan - 1year (365 days) 27. Traffic Flow Forecasting: The task for this dataset is to forecast the spatio-temporal traffic volume based on the historical traffic volume and other features in neighboring locations. 28. UJIIndoorLoc-Mag: The UJIIndoorLoc-Mag is an indoor localization database to test Indoor Positioning System that rely on Earth's magnetic field variations. 29. Water Quality Prediction: The goal is to predict the spatio-temporal water quality in terms of the “power of hydrogen (pH)” value for the next day based on the historical data of water measurement indices. 30. Wave Energy Converters: This data set consists of positions and absorbed power outputs of wave energy converters (WECs) in four real wave scenarios from the southern coast of Australia. 31. Wave Energy Converters: This data set consists of positions and absorbed power outputs of wave energy converters (WECs) in four real wave scenarios from the southern coast of Australia. 32. 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. | 
