DataFlash: 2020 RDAP

Posted by Nancy Shin on March 18th, 2020 Posted in: Blog, Data Science, Health Literacy, Public Health, Training & Education
Tags: Be FAIR and CARE, GIDA, nnlm pnr, rdap

This past March 2020 RDAP was hosted in Santa Fe, New Mexico.  Unfortunately, I was not able to attend in person, but I was able to catch the conference virtually.  The keynote speaker was incredibly informative and knowledgeable and of course, very articulate and engaging.  For me, the highlight of the Summit was the keynote speaker.  The conference keynote was Michele Suina, PhD (Cochiti Pueblo), Program Director, Albuquerque Area Southwest Tribal Epidemiology Center (AASTEC).

Michele talked about her work with the Global Indigenous Data Alliance (GIDA) which is a great organization that prides themselves on “promoting indigenous control of indigenous data” around the world.  Their data motto is “Be FAIR and CARE” which is a play on the popular data acronym FAIR (i.e. fair, accessible, interoperable, and reusable) and GIDA’s acronym for data CARE.

CARE is an acronym that reminds us that right because data is shared and open doesn’t necessarily mean that it’s tension-free for all people especially vulnerable populations like indigenous ones.  Let’s take a closer look at what CARE means.  The “C” in CARE stands for “Collective benefit” which means that data should be used in ways that empower Indigenous People so that they can derive maximum benefit from the data’s use.  The “A” in CARE stands for “Authority to control” which means we must recognize the rights and interests of Indigenous Peoples and their rights and interests over their data; in other words, we must respect their authority to control their own data. The “R” in CARE stands for “Responsibility” which means that we are responsible and accountable for how the data is being used to foster positive relationships with the Indigenous Peoples and that they derive the maximum benefit from their data. The “E” in CARE stand for “Ethics” which means that the wellbeing of the Indigenous Peoples should always be at the heart of the data life cycle and across data ecosystems.

As data enthusiasts we must remember that to be “FAIR”, we must also “CARE” especially with vulnerable populations like indigenous ones.

ABOUT Nancy Shin
I received my Bachelor of Science in the Integrated Sciences majoring in medical genetics and animal biology from the University of British Columbia (UBC). I also graduated from UBC's esteemed MLIS program with a focus on health librarianship. In 2018, I was the Research Data Management Sewell Fund Fellow for the Technology Incubator at Washington State University. Currently, I'm the NNLM Region 5's Outreach and Data Coordinator for the University of Washington's Health Sciences Library. In my spare time, I enjoy photography, drawing, cooking and baking, and travelling the world!!!

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