Scope and Purpose
This guide is intended to help find (a) primary and secondary data and datasets documenting racism and the Black experience internationally, as well discrimination based on indigenous, national, and cultural or ethnic origins and (b) tools, articles, and rubrics for building anti-racism into the process of working with data across the data-research lifecycle.
The guide is accompanied by other resources developed by the IASSIST Anti-Racism Resources Interest Group:
- Datasets, projects, and data sources for racial justice (in .csv format)
- Tools, articles, and rubrics for working with data through an anti-racism lens (in .csv format)
- How Different Countries View Race essays and webinar
While the strategies and techniques given are initially oriented toward this original scope, the list of suggested terms can be adapted and expanded over time to address other types of discrimination, such as by migrant/refugee status, religion, gender identity, or sexuality.
The guide is organized into three sections
Ethics and Best Practices
Lists some tools and guides to raise awareness and for best practices in integrating an anti-racism lens throughout the data lifecycle.
Sources and Strategies
Organizes data sources into nine sets. Within each set of sources, there are suggested strategies and specific techniques and examples.
Concepts and Context
Concepts, ownership and access rights to data, suggested search terms, and guidance for collecting and analyzing data.
In more details the three sections cover the topics as follows:
Ethics and Best Practices lists some tools and guides to raise awareness and for best practices in integrating an anti-racism lens throughout the data lifecycle.
Sources and Strategies organizes data sources into nine sets. Within each set of sources, there are suggested strategies and specific techniques and examples. While the examples shown here often highlight racial justice topics in the US, these strategies can be used to discover data against other groups and for different topics in other countries. Multiple strategies will need to be deployed. If you cannot find something using this guide and the accompanied resources lists, reach out to libraries, organizations, or researchers for help.
Concepts and Context covers four areas that apply to all the sources and strategies: (a) concepts like statistics or aggregate data from microdata; (b) ownership and access rights to data for use and protection for individuals and communities; (c) suggested search terms and language; and (d) guidance for collecting and analyzing data through an anti-racism lens.
A more detailed table of contents is also available.
Feedback and Suggestions
This guide is a work in progress and suggestions and feedback on sources, strategies, and techniques for finding and accessing harmonized, inclusive, and international anti-racism resources would be welcome to contribute to making this guide inclusive and applicable internationally.
Please submit feedback to our Feedback and Suggestions Form .
IASSIST Anti-Racism Resources Action Group Finding Data Guide Subgroup authors (May 2023)
- Jenny McBurney, University of Minnesota - Twin Cities (USA)
- Jennifer Boettcher, Georgetown University (USA)
- Kevin Manuel, Toronto Metropolitan University (Canada)
- Ryan Womack, Rutgers University (USA)
- Van Bich Tran, Temple University (USA)
- Anja Perry, GESIS – Leibniz Institute for the Social Sciences (Germany)
Other contributors to this guide:
- Michele M. Hayslett, University of North Carolina at Chapel Hill (USA)
- Nancy Kassam-Adams, Children’s Hospital of Philadelphia (USA)
- Bobray J. Bordelon, Princeton University (USA)
- Barbara Levergood, Bowdoin College (USA)
- Lacey Cain, Carleton University (Canada)
We apologize if your name has not been included. Please let us know if you have contributed.
This work is licensed under CC BY 4.0 .
Diversity, Equity, and Inclusion Data Resources Interest Group. 2023. Guide to Finding Data about Racism and Ethnic Bias. https://iassistdata.org/community/antiracism-resources-guide/ (CC BY 4.0)