Code of Conduct - DSF

Data Science Fellows Code of Conduct

The Data Science Fellows program serves as part of the University of Arizona Strategic Initiative, UA Health Sciences 5.3, Health Analytics Powerhouse for Health and Life Sciences. The vision is to establish a powerhouse for health analytics by creating and supporting a robust data-rich ecosystem that has minimal friction at the boundaries of technology, compliance, and usage. The mission is empowering research teams to collaborate using contemporary data science tools and technologies in a productive computational environment.

The Data Science Fellows program is for Graduate level researchers.  Fellows participate in a dynamic environment to develop, exchange, and create data science expertise needed to solve cutting edge research problems in health sciences.  Fellows receive intensive training and mentoring focused on the use of open science and computational infrastructure, such as CyVerse, to apply data science tools to their research.

The nature of the Data Science Fellows program is collaborative with a focus on open science and reproducibility. We strive to create and foster an environment of psychological safety so that everyone feels comfortable sharing ideas and contributing to conversation. By joining the Data Science Fellows program, you must agree to the principles and code of conduct, detailed below.


We provide a welcoming and supportive environment for all involved with Data Science Fellows program, regardless of race, religion, background, nationality, gender-identity, sexual orientation, age, disability or any other identity. By participating in the program, you agree to contribute to making it respectful and inclusive. Harassment or bullying will not be tolerated.  Any form of behavior or language intended to exclude, intimidate, or cause discomfort is a violation of the code of conduct.

Behavior encouraged to create a positive and professional environment include:

  • Using welcoming, inclusive language
  • Be respectful and open to differing viewpoints and experiences
  • Leverage the variety of backgrounds unique to each postdoc in the program
  • Practice open, honest, and respectful communication
  • Be open-minded and receptive to constructive criticism

If a problem or concern arises, please contact:
Rudy Salcido at or Maliaca Oxnam at Report more serious matters through the appropriate campus resource.

Data Management

This program involves a focus on open, reproducible science.  While there are no specific rules on data management work plans, it is expected that Fellows adhere to best practices as the suit them, striving to maintain the highest level of open science principles they can manage. It is encouraged that Fellows version control and thoroughly document their work with readme files, GitHub, R markdown, or similar techniques so it is intelligible and accessible in the future, with the intention of eventually publishing work and data to public repositories.  FAIR data management practices should be followed as much as possible.

Role Expectations

Faculty Responsibilities to Fellows:

  • Provide opportunities for networking and professional development
  • Create space for constructive conversations about relevant data science issues
  • Foster a safe, inclusive environment in which all feel able to share

Expectations of Fellows:

  • Fellows are expected to attend and participate in all the twice weekly training activities for the semester. FOSS sessions take place every Thursday from 11:00 am to 1:00 pm. The following Tuesday of each week from 11:00 am to 1 pm will be an applied health science focused discussion on the topic from the previous FOSS session and an opportunity to follow-up on the content.
  • A weekly update via a GitHub repository will be due every Monday at 12:00 pm.  
  • Fellows are expected to attend orientation activities.
  • Fellows are expected to attend virtual training sessions and in-person activities as determined by the cohort.
  • Meet with lab PI or advisors regularly to discuss application of content learned from the program.
  • Participate in program discussions and events.

Additionally, a fellow in the Data Science Fellows program is expected to be an outstanding example and role model in the data science field. Fellows should be committed to community engagement, passionate about data science in health sciences, and continue to demonstrate and spread best practices in data management.