Reviewing Reproducible Code in Gigantum

Posted by The Gigantum Team on May 18, 2020 5:16:07 PM

This post is a high-level overview to show how to Gigantum to inspect code for a manuscript under review. 

Gigantum is a browser-based platform that makes it easy to create, manage and share versioned and fully reproducible computational work without extra effort. It supports reproducibility and replication for work done in Jupyter, JupyterLab and RStudio. You can learn more about it in our docs.

Reviewers will use Gigantum to inspect submitted code to better determine how it supports the research manuscript under review. While code review will be done in Gigantum, the rest of the review process and communicating with the Editor is done through the channels designated by the Editor.

Code Review in Gigantum

Gigantum provides a simple and transparent way to examine and run code for peer review. Reviewers get their own independent copy of the submitted code, and their work is private.

Accessing and Inspecting the Code

When you agree to review the manuscript, you will get a link to a Gigantum cloud instance that has the code already loaded for your review.

To start, click the link and your browser will take you a cloud instance where you will see the code loaded in a Gigantum Project. The Project will have a meaningful name related to the manuscript. During the review process, all of your work on this code is private. 

The code will be available either as a collection of Jupyter notebooks or R Markdown files in RStudio. To run the code, do the following:

  1. Click the Project card for the submitted code and inspect the Read Me file
  2. Launch an execution environment with the blue Launch button to open a tab with a live execution environment.
  3. Note: You will need to allow pop-ups in your browser in order for the new tab to open. Look for a notification in the search / URL bar! See here for instructions.
  4. Note: If it didn’t work after allowing pop-ups, then may have an ad-blocker interfering with Gigantum. Here is how to fix that.

The video shows the launching a JupyterLab environment, but the default environment depends on the Project. 

Once the execution environment is running you can inspect and run the code as you like. To stop the execution environment, click the status toggle next to the Launch button. This will change the status from Running to Stopped.

Using the Activity Feed

You can see the Project's history in the Activity Feed, which is an interactive linear history of all user actions including:

  • Environment creation and modification
  • File uploads
  • Individual cell executions, including data used and outputs



It has time-stamped and username-attributed entries that provide details not visible when inspecting the notebooks. Each entry is a snapshot of specific actions at a specific time, ranging from adding packages and files, to the execution and output of each individual Jupyter cell. This integrated tracking system means that you can see all relevant events in order and with great detail even without running the code. If the Project was constructed and executed properly, the Activity Feed should be sufficient to understand and validate what the code does.

You can read more about it here and here.

Learn More!

This was a brief overview of the process necessary to review code in Gigantum. Check out other user-friendly features not featured in this post:

Learn more about Gigantum in our docs or on our blog. You can also email us at and follow us on Twitter at @gigantum_science.


Topics: Reproducibility, Open Science, Peer Review