Indigenous DataSET

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Indigenous Data Sovereignty and Ethics Training

A Year-Long Indigenous Data Sovereignty & Ethics Training for 15 Early Career Faculty in Arizona

Equipping researchers to advance Indigenous Data Sovereignty & Governance

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DEADLINE: NOV. 15, 2025

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Funded by the American Indian Research Centers for Health at the Inter Tribal Council of Arizona and organized by the top Indigenous Data Sovereignty and Governance experts in the U.S. at the Collaboratory for Indigenous Data Governance led by Dr. Stephanie Russo Carroll, Indigenous DataSET aims to fill knowledge gaps in the ethics and infrastructure for research that impacts Indigenous rights holders to promote a future of more equitable science practices. Ultimately, the project aspires to protect Indigenous communities and their data by enhancing Tribal research and data governance in Arizona.

In pursuit of this goal, the Indigenous DataSET team is looking to recruit 15 early career faculty (post-doc through assistant-professor level) in any discipline from public universities (ASU, NAU, and U of A) and Tribal colleges across Arizona to participate as 2026 Indigenous DataSET Fellows.

Any and all early career faculty who will be employed by the University of Arizona, Arizona State University, Northern Arizona University, Diné College, San Carlos Apache College, Navajo Technical University and Tohono O’odham Community College during the 2026 academic year are invited to apply for an Indigenous DataSET Fellowship by November 18, 2025.

Researchers with any level of knowledge and experience in the fields of Indigenous Data Sovereignty (IDSov) and Indigenous Data Governance (IDGov) – including those with no previous exposure to these subjects – are eligible.

2025-26 Indigenous DataSET Fellowship Structure and Schedule

Indigenous Peoples and their communities have been targets of extractive research practices for centuries. And, in the absence of comprehensive guidelines, standards, and laws outlining how ethical research involving Indigenous subjects is to be performed and how Indigenous data and knowledge are to be used, questionable practices persist in this area today.

As a Indigenous DataSET Fellow, you will be equipped over the course of the 2026 academic year with the knowledge, tools, and perspectives necessary to conduct research and steward data in ways that comport with the Arizona Board of Regents Tribal Consultation Policy, university policies, and Indigenous Peoples’ rights and interests. After six months of education and discussion, you will also have the opportunity to participate in a national Indigenous Data Sovereignty gathering.

As part of the program, each Indigenous DataSET Fellow will design and complete a year-long project that advances Indigenous Data Sovereignty and Governance within their field of study. Fellows will receive ongoing guidance from the project team, with opportunities to address questions and refine their work throughout the year. To strengthen connections and provide timely feedback, Fellows may also join weekly optional chats, which have proven valuable for building community and fostering collaboration. Fellows will also be required to attend mandatory quarterly check-ins via Zoom. 

PROGRAM DATES: Jan. - Dec. 2026 

All dates/times will be TBD with Fellows

  • Optional Weekly Meetings Online 
    Network with your Fellowship peers and mentors during optional weekly meetings via Zoom.


QUARTER 1 

  • Indigenous DataSET program launch & kick-off event Online 

  • Training on Indigenous Data Sovereignty & Governance Online 

  • Mandatory project identification with project team Online 


QUARTER  2 

  • U.S. Indigenous Data Sovereignty & Governance Summit 2026 in Tucson, AZ  In-person 
    Engage Tribal leaders, staff, community practitioners, and Tribally-engaged researchers in Arizona on IDGov topics (may include opportunities to present and/or participate in expert panel discussions)

  • Mandatory Project Check-in Online 


QUARTER 3 

  • Mandatory Project Check-in Online 


QUARTER 4 

  • Mandatory Project Check-in Online 

How to Apply

To apply for the Indigenous DataSET Fellowship, you’ll need to provide:

-1-

Basic information such as your name, appointment and Indigenous affiliation (if applicable)

-2-

Your current CV

-3-

A letter of recommendation from a professional colleague or mentor

Letter (in pdf format) must speak to your values, work ethic, professional integrity, and commitment to Indigenous communities

-4-

Answers to the following short-answer questions:

  • Will you be a postdoc or early career faculty at a public university (ASU, NAU, UArizona) or Tribal college in Arizona for the 2025-2026 academic year?
  • Can you commit to attending all the Indigenous DataSET sessions during the 2025-2026 academic year?
  • Do you have any accessibility needs, including dependent care, language, mobility, vision, connectivity?
  • This program is intended for people with any level of knowledge and experience with Indigenous Data Sovereignty and Governance, and research with Indigenous communities. How familiar are you with Indigenous Data Sovereignty and Governance? Have you had previous exposure and training to Indigenous Data Sovereignty and Governance? If so, what? (Please keep responses to approximately 100-200 words)
  • How might Indigenous Data Sovereignty and Governance support your vision for your research and long-term career goals? (Please keep responses to approximately 100-200 words)
APPLY NOW

DEADLINE: NOV. 15, 2025

Questions?

Please contact Andrew Martinez andrewmartinez@arizona.edu with any questions. 

 


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Intertribal Council of Arizona

 

 

ITCA is pleased to take park in this collaborative project with the University of Arizona Indigenous DataSET Training Program, ITCA serves as the administrative support for the work of the project.

This work is funded by the National Institutes of Health grant ITCA NARCH XII (S06GM146125), as a Faculty/Researcher Career Enhancement Project entitled Enhancing early career research ethics to support Indigenous data governance in Arizona.

 

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