The FAIR Guiding Principles for scientific data management and stewardship were first published in 2016. They are intended to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. The FAIR principles emphasize machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.
Making research data more FAIR can provide a range of benefits to researchers, research communities, research infrastructure facilities, and research organizations, such as increasing research impact, visibility, citations, reproducibility, and reliability. The Principles are also referenced as a quality and stewardship standard within many data management and sharing policies, including the NIH data management and sharing policy.
Visit the links below to learn more about the FAIR Principles and how to implement them.
Research data that contain Protected Health Information(PHI) must be de-identified before sharing. Guidance on the HIPAA Privacy Rule in Research is linked below. More resources providing practical guidance for de-identifying data can be found in the Sharing Data section of this guide.
The current movement toward open data and open science does not fully engage with Indigenous Peoples' rights and interests. Existing principles within the open data movement (e.g., FAIR: findable, accessible, interoperable, reusable) primarily focus on data characteristics that will facilitate increased data sharing among entities while ignoring power differentials and historical contexts. The emphasis on greater data sharing alone creates tension for Indigenous Peoples who are also asserting greater control over the application and use of Indigenous data and Indigenous Knowledge for collective benefit.
This includes the right to create value from Indigenous data in ways that are grounded in Indigenous worldviews and realize opportunities within the knowledge economy. The CARE Principles for Indigenous Data Governance are people and purpose-oriented, reflecting the crucial role of data in advancing Indigenous innovation and self-determination. These principles complement the existing FAIR principles encouraging open and other data movements to consider both people and purpose in their advocacy and pursuits.
CARE stands for:
Visit the links below for more detailed information about the CARE Principles.