We designed a privacy-aware VR interface that uses differential privacy, which we evaluate on a new 20-participant dataset for two privacy sensitive tasks.

The data consists of eye gaze as participants read different types of documents.

The dataset consists of a .zip file with two folders (Eye_Tracking_Data and Eye_Movement_Features), a .csv file with the ground truth annotation (Ground_Truth.csv) and a Readme.txt file. In each folder there are two files for participant (P) for each recording (R = document class). These two files contain the recorded eye tracking data and the corresponding eye movement features. The data is saved as a .npy and .csv file. The data scheme of the eye tracking data and eye movement features is given in the Readme.txt file.

The data is only to be used for non-commercial scientific purposes.