The research happening at universities, labs, research facilities, private and public companies, and government institutions around the world will change lives, which is why we believe institutions should not have to think twice about how to manage the large amounts of data collected by their researchers.

Research data sharing is critical to scientific innovation and reproducible research. IEEE is committed to supporting the data sharing needs of the research community. IEEE developed IEEE DataPort, a unified data storage and collaboration platform for institutions, where all members of an organization can store, share, access, and manage research data, accelerating research efforts at your institution.


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Features

Features & Benefits:

All IEEE DataPort institutional subscriptions offer the following organization-wide benefits:

  • Access all datasets (both Open Access and non-Open Access datasets) on IEEE DataPort to advance your research
  • Gain global exposure for research led by your institution
  • Meet research funding agency requirements for publishing data and making data available on an open access basis
  • Host data in any format, from video, audio, and image files to CSV and TXT files
  • Consolidate your institution’s research data in one trusted location with cloud storage up to 10TB per dataset
  • Enable open access uploads with a premium institutional subscription
  • Access custom usage dashboards for your institution which show datasets uploaded by your institution and those using IEEE DataPort from your institution
  • Brand your datasets uploaded by your institution with your institution’s logo to increase exposure and recognition of your valuable research

3D Printing Liquid Metal to Create Stretchable Electonic Devices

23 Jan 2019

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As 5G Wireless Rolls Out, Experts Look Ahead to 6G

17 Jan 2019

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Hand-Tracking Tech Is Taking Self-Driving Cars to the Next Level

5 Dec 2019

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Author 1
Frede Blaabjerg

(AALBORG, DENMARK)

Harmonic Stability in Power Electronic Based Power Systems: Concept, Modeling, and Analysis

Author 2
Irith Pomeranz

(INDIANA, US)

Extra Clocking of LFSR Seeds for Improved Path Delay Fault Coverage

Author 3
Manan Suri

(DELHI, INDIA)

Performance Enhancement of Edge-AI-Inference Using Commodity MRAM: IoT Case Study

Terms and Conditions

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