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Research Guides

Research Data Management: Prepping: Ethical Considerations

Guide of resources related to the many aspects of research data management. Data management encompasses the processes surrounding collecting, organizing, describing, sharing, and preserving data.

What will I find in this guide?

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How might I be responsible to other researchers?

You are responsible to a number of different communities throughout the research data lifecycle. As a responsible steward of your data, you should consider the ethical decisions you will need to make around your data as early into data management as possible.

As you generate new knowledge in your field, think about the research outputs you create. One way you can frame this question is to think about your responsibility to the broader research community. How can you ensure the data you publish enables more inclusive research, transparency, and sustainability?

The FAIR Guiding Principles for scientific data management and stewardship are a set of guidelines to ensure the ethical (re)use of research data. The guidelines seek to increase the Findability, Accessibility, Interoperability, and Reuse of digital assets.

  • Findable: Your machine-readable metadata makes your data easy to find for both humans and computers.
  • Accessible: Your data and metadata can be accessed once it has been found. 
  • Interoperable: You data can be integrated with other data and can be interoperated with applications or workflows for analysis, storage, and processing
  • Reusable: You data is well-described so that it can be replicated and combined

Learn more about how to make your data align with the FAIR principles.

How might I be ethically responsible to those my data is for or from?

Anti-Racism & Research Data Management

One way to work responsibly with data is to acknowledge that data is not objective. While individual data points may seem objective, methods of data collection, subject recruitment, analysis, and any other stages of the data lifecycle where humans are involved are all moments where biases are introduced.

Historically and currently, Western research practices center whiteness and frequently create disparities for and harm BIPOC scholars and research participants.

The following resources are starting points for applying an anti-racism lens to your data management practices:


The University of Minnesota's guide to conducting research through an anti-racism served as a resource for compiling this list.

Indigenous Data Sovereignty

When you work with Indigenous communities and their data, Indigenous data sovereignty should be core to your data management practices. Indigenous data sovereignty refers to the right of Indigenous communities to govern the collection, ownership, and application of their own data. The CARE Principles were developed to provide a guide for Indigenous data management and stewardship:

  • Collective Benefit: Ensuring that the purpose of the data is for equitable outcomes and innovation
  • Authority to Control: Ensuring the Indigenous rights and interests are recognized and the governance over the collection, ownership, and application of Indigenous data belongs to Indigenous people
  • Responsibility: Emphasizes the responsibility to Indigenous languages and worldviews and building positive relationships of trust between Indigenous communities and researchers
  • Ethics: Ensuring that the collection and application minimizes harm while maximizing benefits for Indigenous people

The following resources are starting points for working responsibly with Indigenous communities and data:

Tools & Resources


If you have questions about ethical data management or would like to request a consultation with a member of the Scholarly Communications and Publishing Team, please email