Research Data Management Guide

This guide is intended to assist you in topics of planning, collecting, cleaning, preserving, and and sharing research data.

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Erin Owens
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NGL 223D

Some Principles of Data Ethics

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 full and summary principles documents on the GIDA website provide significantly more detail, but in summary:

  • Collective Benefit: Data ecosystems shall be designed and function in ways that enable Indigenous Peoples to derive benefit from the data.
  • Authority to Control: Indigenous Peoples’ rights and interests in Indigenous data must be recognised and their authority to control such data be empowered. Indigenous data governance enables Indigenous Peoples and governing bodies to determine how Indigenous Peoples, as well as Indigenous lands, territories, resources, knowledges and geographical indicators, are represented and identified within data.
  • Responsibility: Those working with Indigenous data have a responsibility to share how those data are used to support Indigenous Peoples’ self-determination and collective benefit. Accountability requires meaningful and openly available evidence of these efforts and the benefits accruing to Indigenous Peoples.
  • Ethics: Indigenous Peoples’ rights and wellbeing should be the primary concern at all stages of the data life cycle and across the data ecosystem.

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."

 

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