Brought to you by NumFOCUS Foundation and O’Reilly Media
The official Jupyter Conference
Aug 21-22, 2018: Training
Aug 22-24, 2018: Tutorials & Conference
New York, NY
Jackson Brown

Jackson Brown
Research Engineer, Allen Institute for Cell Science

Website

Jackson Brown is a research engineer working on data release infrastructure for the modeling team at the Allen Institute for Cell Science. He is also the cofounder of the Council Data Project, an organization working to enable better public transparency and discourse. Previously, he was a designer for SageMathCloud (CoCalc), a collaborative computation service.

Sessions

11:05am–11:45am Friday, August 24, 2018
Reproducible data dependencies for Jupyter: Distributing massive, versioned image datasets from the Allen Institute for Cell Science
Enterprise and organizational adoption, Extensions and customization, Reproducible research and open science
 Location: Sutton Center/Sutton South Level: Intermediate
Jackson Brown (Allen Institute for Cell Science), Aneesh Karve (Quilt)
Average rating: *****
(5.00, 3 ratings)
Reproducible data is essential for notebooks that work across time, across contributors, and across machines. Jackson Brown and Aneesh Karve demonstrate how to use an open source data registry to create reproducible data dependencies for Jupyter and share a case study in open science over terabyte-size image datasets. Read more.