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Community-driven data science practices

Atilio Barreda, Carrie Diaz Eaton, Sam Hansen, Joseph E. Hibdon, Lee T. Gordon, Rebekah Greenwald, María José Gutiérrez Paz, Kenan İnce, Claire Kelling, Drew Lewis, Ariana Mendible, Jenny Mercado, Victor Piercey, Bianca Thompson

TL;DR

This paper investigates two co-authored community-research partnerships—VECINA and SToPA—that pair mathematicians with community members to advance data-science-for-social-justice goals. It introduces a power-process-perspective framework and uses duoethnography to reveal researchers' lived experiences, offering a practical blueprint for equitable collaboration. The work demonstrates how open-source tools, shared ownership, and capacity-building enable place-based environmental and policing justice projects to scale beyond a single community. It also discusses challenges such as funding and institutional constraints, and highlights the potential for more ethical, impactful mathematical research when communities lead data-driven inquiries.

Abstract

Mathematics researchers are becoming more involved with research questions at the interface of data science and social justice. This type of research needs to be grounded in the needs of the community in order to have significant impact. In this paper, we examine two examples of community-research partnerships in data science for social justice co-authored by both community members and mathematical researchers. The first, VECINA, is a place-based community-research partnership focused on environmental justice. VECINA introduces a framework for developing fruitful local collaborations. The second example, SToPA, originates in citizens' request for an analysis of their town's policing data, but focuses on how to scale this work beyond that place-based setting. SToPA's research helps us imagine how we can continue to actively collaborate with community members even when working to scale projects beyond a single community. In both of these case studies, we examine the harmonies between established principles of power, process, and perspective with our framework for research-community partnerships. We use a duoethnography approach, directly illustrating the experiences of researchers. We also offer a set of reflections on the impact of these research-community partnerships.

Community-driven data science practices

TL;DR

This paper investigates two co-authored community-research partnerships—VECINA and SToPA—that pair mathematicians with community members to advance data-science-for-social-justice goals. It introduces a power-process-perspective framework and uses duoethnography to reveal researchers' lived experiences, offering a practical blueprint for equitable collaboration. The work demonstrates how open-source tools, shared ownership, and capacity-building enable place-based environmental and policing justice projects to scale beyond a single community. It also discusses challenges such as funding and institutional constraints, and highlights the potential for more ethical, impactful mathematical research when communities lead data-driven inquiries.

Abstract

Mathematics researchers are becoming more involved with research questions at the interface of data science and social justice. This type of research needs to be grounded in the needs of the community in order to have significant impact. In this paper, we examine two examples of community-research partnerships in data science for social justice co-authored by both community members and mathematical researchers. The first, VECINA, is a place-based community-research partnership focused on environmental justice. VECINA introduces a framework for developing fruitful local collaborations. The second example, SToPA, originates in citizens' request for an analysis of their town's policing data, but focuses on how to scale this work beyond that place-based setting. SToPA's research helps us imagine how we can continue to actively collaborate with community members even when working to scale projects beyond a single community. In both of these case studies, we examine the harmonies between established principles of power, process, and perspective with our framework for research-community partnerships. We use a duoethnography approach, directly illustrating the experiences of researchers. We also offer a set of reflections on the impact of these research-community partnerships.
Paper Structure (13 sections, 4 figures, 1 table)

This paper contains 13 sections, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. Nuevas Voces, WRWC and VECINA
  3. Perspective
  4. Process
  5. Power
  6. Products and Relationships
  7. SToPA
  8. Perspective
  9. Process
  10. Power
  11. Products and Relationships
  12. Impact
  13. Challenges and Opportunities

Figures (4)

  • Figure 1: Framework developed during the IMSI research semester for research-community partnerships adapted from the Bonner Framework (www.bonner.org). We explain how the established principles of power, process, and perspective connect to this framework through the case studies. See Table \ref{['tab:framework']} for further elaboration on our framework.
  • Figure 2: The Woonasquatucket - Algonquian name meaning “where the salt water ends” - runs through downtown Providence, RI and into the Narragansett Bay. Brown University (in College Hill) and ICERM (in Downtown, just west of College Hill) are located to the east of the river, while Olneyville (highlighted with purple diagonal lines) is a neighborhood bordering the river to the west of the bay.
  • Figure 3: Screenshot of Leaflet StoryMap showing testing outcome disparities between ELL and non-ELL students. The ES symbol in the upper left by the school name indicates that this school has specialized programming for ELL students.
  • Figure 4: A draft version of the interactive directory for the SToPA toolkit, where users will be able to find more information about how to obtain, clean, utilize, analyze, and act on findings from public data.