Academics Torrents was founded to address the needs of science in the era of big data. It is a scalable platform using BitTorrent which distributes the cost of hosting data in order to prevent the rise and fall of dataset hosting providers and the erasure of the data they host. Researchers are empowered to mirror data they are working with and share large datasets without the large costs typically associated with commercial providers.

Academic Torrents is a product of the Institute for Reproducible Research (a U.S. 501(c)3 nonprofit).


Joseph Paul Cohen        Henry Z Lo        Jonathan Nogueira


Personal Statement

  • This service is designed to facilitate storage of all the data used in research, including datasets as well as publications. There are many advantages of using bittorrent technology to disseminate this work.

  • Distributed storage and content delivery provided by anyone. Files can be securely downloaded from other users of the system. They can share the file for a day or a year.

  • Mirroring the content can be done from a desktop computer anywhere. Everyone surrounding this computer will have local access to the data automatically and securely.

  • Bundles of files, not just papers, or any size can be disseminated in this way as long as at least one person can become a seed for that data.

  • Torrent technology allows a group of editors to “seed” their own peer-reviewed published articles with just a torrent client. Each editor can have part or all of the papers stored on their desktops and have a torrent tracker to coordinate the delivery of papers without a dedicated server.

  • One aim of this site is to create the infrastructure to allow open access journals to operate at low cost. By facilitating file transfers, the journal can focus on its core mission of providing world class research. After peer review the paper can be indexed on this site and disseminated throughout our system.

  • Large dataset delivery can be supported by researchers in the field that have the dataset on their machine. A popular large dataset doesn’t need to be housed centrally. Researchers can have part of the dataset they are working on and they can help host it together.

  • Libraries can host this data to host papers from their own campus without becoming the only source of the data. So even if a library’s system is broken other universities can participate in getting that data into the hands of researchers.

-Joseph Paul Cohen 2013 joseph /at/ josephpcohen.com


Please cite Academic Torrents:

  • Henry Z. Lo. and Cohen, Joseph Paul “Academic Torrents: Scalable Data Distribution.” Neural Information Processing Systems Challenges in Machine Learning (CiML) Workshop, 2016, http://arxiv.org/abs/1603.04395.

  • Cohen, Joseph Paul, and Henry Z. Lo. “Academic Torrents: A Community-Maintained Distributed Repository.” Annual Conference of the Extreme Science and Engineering Discovery Environment, 2014, http://doi.org/10.1145/2616498.2616528.

download bibtex file academictorrents.bib

title = {Academic Torrents: A Community-Maintained Distributed Repository},
author = {Cohen, Joseph Paul and Lo, Henry Z.},
booktitle = {Annual Conference of the Extreme Science and Engineering Discovery Environment},
doi = {10.1145/2616498.2616528},
url = {http://doi.acm.org/10.1145/2616498.2616528},
year = {2014}

title = {Academic Torrents: Scalable Data Distribution},
author = {Lo, Henry Z. and Cohen, Joseph Paul},
booktitle = {Neural Information Processing Systems Challenges in Machine Learning (CiML) workshop},
arxivId = {1603.04395},
url = {http://arxiv.org/abs/1603.04395},
year = {2016}


If you are having issues, please let us know
We have an issue tracker here: https://github.com/AcademicTorrents/academictorrents-docs/issues
We have a contact email here: contact@academictorrents.com


Python at-python library

Martin Weiss

Smart Node Team 2014

Jonathan Nogueira, Adrian Garay, Grigorii Lazari, James Lee, Luc Nguyen, Mani Jalilian, Edward Grigoryan

Java BitTorrent API Team 2015

Alpesh Kothari, Gregory McPherran


akmalhisyam, Mantas Radzevičius, Stefan Parviainen, Hanz Gumapac