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. 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.
3. 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.
4. Appliances energy prediction: Experimental data used to create regression models of appliances energy use in a low energy building.
5. 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
6. BitcoinHeistRansomwareAddressDataset: BitcoinHeist datasets contains address features on the heterogeneous Bitcoin network to identify ransomware payments.
7. 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.