1. Predict keywords activities in a online social media: The data from Twitter was collected during 360 consecutive days. It was done by querying 1497 English keywords sampled from Wikipedia. This dataset is proposed in a Learning to rank setting.
2. 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.
3. 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
4. Appliances energy prediction: Experimental data used to create regression models of appliances energy use in a low energy building.
5. 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.
6. 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.
7. BitcoinHeistRansomwareAddressDataset: BitcoinHeist datasets contains address features on the heterogeneous Bitcoin network to identify ransomware payments.