At the turn of the century, Joel Spolsky came up with the idea of a “Joel Test” – a highly irresponsible, sloppy test to rate the quality of a software team.

Then, this group thought to come up with their own criteria to rate the quality of a data science team.  How do your analysts in the radiology department fare?

The “Joel Test” for Data Science

1. Can new hires get set up in the environment to run analyses on their first day?
2. Can data scientists utilize the latest tools/packages without help from IT?
3. Can data scientists use on-demand and scalable compute resources without help from IT/dev ops?
4. Can data scientists find and reproduce past experiments and results, using the original code, data, parameters, and software versions?
5. Does collaboration happen through a system other than email?
6. Can predictive models be deployed to production without custom engineering or infrastructure work?
7. Is there a single place to search for past research and reusable data sets, code, etc?
8. Do your data scientists use the best tools money can buy?

Howard Chen

Associate Informatics Officer at Cleveland Clinic Imaging Institute

(Howard) Po-Hao Chen, MD MBA is the Associate Informatics Officer at the Cleveland Clinic Imaging Institute and a musculoskeletal radiology subspecialist. He has an interest in data-driven radiology, quality improvement, and innovation. Howard has an MD and MBA from Harvard University, and he finished training with fellowships in musculoskeletal radiology, nuclear medicine, and clinical imaging informatics in June 2018 from University of Pennsylvania.