"Many people think of data-driven research as something that (only) happens in the sciences....(resulting in) a spreadsheet filled with numbers. Both of these beliefs are incorrect. Research data are collected and used in scholarship across all academic disciplines and, while it can consist of numbers in a spreadsheet, it also takes many different formats..."(Macalester College Library. Defining Research Data).
As noted above, researchers in every discipline can generate research data and those data are not limited to numbers in a spreadsheet. Depending on the context any of the following formats may be examples of research data:
In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. Since then the notion that publicly funded research needs to be FAIR has been widely embraced and adopted by the Academy. FAIR data are:
For more information about the FAIR Principles see GO FAIR: How to Go FAIR
|"Existing principles within the open data movement (e.g. FAIR: findable, accessible, interoperable, reusable) primarily focus on characteristics of data that will facilitate increased data sharing among entities while ignoring power differentials and historical contexts. The emphasis on greater data sharing alone creates a tension for Indigenous Peoples who are also asserting greater control over the application and use of Indigenous data and Indigenous Knowledge for collective benefit" (Global Indigenous Data Alliance. CARE Principles for Indigenous Data Governance).|
The CARE Principles for Indigenous Data Governance are designed to complement the FAIR principles and take into account the current and historic power imbalances between researchers and Indigenous communities.
To learn more about the CARE Principles, and other important guidance for those engaging in research for, by, about, and/or with Indigenous individuals, communities, territories or Nations see the Indigenous Data page of this guide.