https://github.com/datalad/talk-2019-mila
A DataLad overview talk at MILA, Montreal 2019
https://github.com/datalad/talk-2019-mila
Last synced: 4 months ago
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A DataLad overview talk at MILA, Montreal 2019
- Host: GitHub
- URL: https://github.com/datalad/talk-2019-mila
- Owner: datalad
- Created: 2019-03-25T19:16:51.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-03-28T13:36:31.000Z (about 7 years ago)
- Last Synced: 2025-09-11T10:32:35.846Z (9 months ago)
- Language: HTML
- Homepage: http://datasets.datalad.org/datalad/artwork/talks/2019-mila/#/
- Size: 5.67 MB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# DataLad
Talk on DataLad's data management capabilities, how it aids open science
efforts and helps achieve improved reproducibility in a FAIR way. Heavily
based on the Bernstein Go Fair talk by Michael Hanke, then with mods for
OpenNeuro kick-off meeting, Stanford, 2018 by Yaroslav O. Halchenko, and
finally expanded for MILA.
URLs in the slides ATM are tuned for offline presentation.
## License
All content is released under the Creative Commons license CC BY-SA 4.0:
https://creativecommons.org/licenses/by-sa/4.0/
## Acknowledgements
The work presented in this talk was supported by a US-German collaboration in
computational neuroscience (CRCNS) project "DataGit: converging catalogues,
warehouses, and deployment logistics into a federated 'data distribution'"
(Halchenko/Hanke), co-funded by the US National Science Foundation (NSF
1429999) and the German Federal Ministry of Education and Research (BMBF
01GQ1411). Additional support was provided by the German federal state of
Saxony-Anhalt and the European Regional Development Fund (ERDF), Project:
Center for Behavioral Brain Sciences, Imaging Platform. This work was further
facilitated by the ReproNim project (NIH 1P41EB019936-01A1).