Welcome to IEEE Dataport

IEEE DataPort™ is an easily accessible repository of datasets, including Big Data datasets.  IEEE DataPort™ is designed to make storage of datasets easier, provide access to valuable datasets across a broad scope of topics, facilitate analysis of datasets, and retain referenceable data for reproducible research.

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  • IEEE Brain Data Bank Challenge - St. Petersburg, Russia

    Terabytes of brain EEG data are available through open sources, collected from tests associated with human cognitive capability, stroke patient recovery, class learning ability, and other social environments, over a wide range of demographics. Some also play with stimulus such as audio, music, video, lights and digital games.  

  • GRSS SAR/PolSAR DATABASE

    Remote sensing of environment research has explored the benefits of using synthetic aperture radar imagery systems for a wide range of land and marine applications since these systems are not affected by weather conditions and therefore are operable both daytime and nighttime.

  • COMPSAC 2017: Big Data Analytics Competition

    IEEE Big Data is proud to announce the next competition in our series of Data Analytics & Visualization Competitions. It will be held at IEEE COMPSAC 2017, 4-8 July 2017 in Torino, Italy, and is open to all attendees of the conference.

  • Tracking Neurons in a Moving and Deforming Brain Dataset

    Advances in optical neuroimaging techniques now allow neural activity to be recorded with cellular resolution in awake and behaving animals.  Brain motion in these recordings pose a unique challenge. The location of individual neurons must  be tracked in 3D over time to accurately extract single neuron activity traces. Recordings from small invertebrates like C.

  • VideoSet

    A new methodology to measure coded image/video quality using the just-noticeable-difference (JND) idea was proposed in [1].  Several small JND-based image/video quality datasets were released by the Media Communications Lab at the University of Southern California in [2, 3]. In this work, we present an effort to build a large-scale JND-based coded video quality dataset.

  • TST Footwear-Based dataset for Fall Detection (TST FB4FD)

    The TST FB4FD dataset contains data acquired through a pair of smart shoes. The smart shoes are specifically designed for fall detection purposes and are equipped respectively with 3 Force Sensing Resistors (FSRs) and an inertial unit.

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IEEE DataPort hosts all types of datasets and all data owners are encouraged to upload their datasets without cost. The goal is to provide a sustainable platform to all data owners so datasets can be stored and retrieved at any time to support your research and/or research of other technical experts. Need help? View detailed instructions on uploading a dataset.

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