Submit a Yellowbrick Paper to the Journal of Open Source Software

[bbengfort]

The Journal of Open Source Software (JOSS) is a developer-friendly journal for research software packages and is affiliated with the Open Source Initiative (OSI) and sponsored by NumFOCUS. For a long time, we've wanted to publish a paper related to Yellowbrick, and this might be a good start.

The paper should be written in Markdown and be between 250-1000 words. Principally, it should contain a summary describing high-level functionality for a non-specialist audience with a clear statement of purpose. It should also include a bibliography and a metadata file that can be read by JOSS reviewers.

High level tasks:

• [x] determine who the authors are
• [x] create a bibliography in paper/paper.bib
• [x] generate the metadata in paper/paper.json with this script
• [x] write outline of the paper
• [x] write first draft of the paper
• [x] review and edit draft
• [x] submit to JOSS

Requirements:

• [x] The software should be open source as per the OSI definition
• [ ] The software should have an obvious research application
• [x] You should be a major contributor to the software you are submitting
• [x] The software should be a significant contribution to the available open source software that either enables some new research challenges to be addressed or makes addressing research challenges significantly better (e.g., faster, easier, simpler)
• [x] The software should be feature complete (no half-baked solutions) Minor, ‘utility’ packages, including ‘thin’ API clients are not acceptable
• [x] Be stored in a repository that can be cloned without registration
• [x] Be stored in a repository that is browsable online without registration
• [x] Have an issue tracker that is readable without registration
• [x] Permit individuals to create issues/file tickets against your repository

[bbengfort]

@rebeccabilbro do you want to start putting together the bibliography and I'll start with the outline and the draft, then we can switch?

[bbengfort]

Significant contribution section:

Yellowbrick is a response to the call for open source visual steering tools. For data scientists, Yellowbrick helps evaluate the stability and predictive value of machine learning models and improves the speed of the experimental workflow. For data engineers, Yellowbrick provides visual tools for monitoring model performance in real world applications. For users of models, Yellowbrick provides visual interpretation of the behavior of the model in high dimensional feature space. Finally, for students, Yellowbrick is a framework for understanding a large variety of algorithms and methods.

[bbengfort]

For the "obvious research application" bullet point, we'll just have to rely on data science and machine learning as having obvious research application, as well as our references for visual analytics, etc.