Image source: Institute of Mathematical Statistics, 2019
In order to support open science and increase access to and reuse of data, proposed best practices emphasize that research data should be FAIR: Findable, Accessible, Interoperable, Reusable
The following resources will help you better understand what FAIR means and how to achieve it.
The Global Indigenous Data Alliance (GIDA) observes that "the current movement toward open data and open science does not fully engage with Indigenous Peoples rights and interests," and they assert "the right to create value from Indigenous data in ways that are grounded in Indigenous worldviews and realise opportunities within the knowledge economy."
The CARE principles ask "researchers and those who manage or control research infrastructures to examine the data lifecycle from a people and purpose orientation. ...These principles complement the existing FAIR principles encouraging open and other data movements to consider both people and purpose in their advocacy and pursuits."