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?

Jump to the topic:

How might I be responsible to other researchers?
How might I be ethically responsible to those my data is for or from?
Managing Data with a lens of anti-racism & Indigenous Data Sovereignty

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:

Conducting Research Through an Anti-Racism Lens
Guide by Shanda Hunt and Amy Riegelman.
Developing anti-racist scholarly practice
Video: Dr. Amanda Sullivan at 4:52:00
Toolkit for Centering Racial Equity Within Data Integration
A toolkit by Actionable Intelligence for Social Policy to applying a lens of racial equity throughout the data lifecycle.

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:

CARE Principles for Indigenous Data Governance
A guide for open data research in affirming Indigenous People's rights and interests
Data Services for Indigenous Scholarship and Sovereignty project
A UW iSchool project developing guidance for implement Indigenous data principles with an Indigenous Data Services Framework
Responsible Management and Sharing of American Indian/Alaska Native Participant Data
The NIH's policy on the Management and Sharing of Indigenous Participant Data

Tools & Resources

CARE Principles for Indigenous Data Governance
A guide for open data research in affirming Indigenous People's rights and interests
Conducting research through an anti-racism lens
The University of Minnesota's guide for researchers who are incorporating anti-racism into their research practices.
FAIR Principles
Guidelines to ensure the discovery and integration of data in the future
more...less...
https://www.go-fair.org/fair-principles/
Toolkit for Centering Racial Equity Within Data Integration
A toolkit by Actionable Intelligence for Social Policy to applying a lens of racial equity throughout the data lifecycle.

Questions?

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 uwlib-scp@uw.edu.