The Problem
Create a commenting extension for JupyterLabs that could be eventually integrated into core.
Create a commenting extension for JupyterLabs that could be eventually integrated into core.
The Team
A team of four Project Jupyter interns
A team of four Project Jupyter interns
My Role and Contributions
As the only designer on our intern team of four, I was responsible for all aspects of the design while working within Project Jupyter branding guidelines. Deliverables included empathy maps, personas, sketches, mockups, icons, and prototypes. I additionally organized both the user research and testing.
As the only designer on our intern team of four, I was responsible for all aspects of the design while working within Project Jupyter branding guidelines. Deliverables included empathy maps, personas, sketches, mockups, icons, and prototypes. I additionally organized both the user research and testing.
Our process:
- problem definition
- user research
- sketching and ideation
- wireframing/prototyping
- user testing and reflection
- user research
- sketching and ideation
- wireframing/prototyping
- user testing and reflection
Problem Definition:
A key element of my teams process was targeting and eliminating ambiguity around our project. The first step then was to redefine our problem based of the user research we conducted to keep our goal clear and user centered.
“Create a commenting extension for JupyterLabs that could be eventually integrated into core.”
Became
When working together on notebooks, collaborators often have recommendations and opinions about code and data. These recommendations have to be relayed outside JupyterLab, and it is hard to quickly convey exactly what needs to be changed and how—especially if the whole team isn’t using Git/GitHub. Due to its current lack of commenting and annotation, teams often find that JupyterLab doesn’t cut it for serious collaboration.
User Research:
Before starting any sketching or ideation, I conducted vigorous market research through interviewing students, professors, and working professionals on their experiences with similar commenting systems. Through this process I compiled a list of pains, concerns and priorities that I referenced regularly throughout my design process. We discovered that...
Users Want:
- a clean, easy to navigate design that didn’t get clogged up when there were a lot of comments on a single document.
-a way to easily track and sort personal comments and annotations through comments to help clarify and notate their own work.
Design Guidelines:
This is an example of a guide I would give to my developers to highlight changes that needed to be made to the prototype to help it look as close to the mockup as possible. I also created variable keys to help streamline font and color choices.
Did it actually work?
As soon as we had a working prototype, my team and I utilized UserBrain, a third party company to connect our product with testers. Often the data collected in these test helped decide our choices for smaller details, such as the reply thread condensation.
The structure and flow established through this extension will become the basis for collaboration between thousands of users. This project’s planning occasionally exceeded the scope of what could be technically accomplished during a summer. In addition to the main extension, options for a global comment hub and a condensed mode were explored and planned and could be expanded upon in the future by other teams.
Final Extension
You can explore our GitHub and use our final extension for JupyterLab here
