CWRU Integrating Community Knowleged and Core Resources in Grad. Certificate Program in DS for Social Impact (DSSI)
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Keywords
Data & Algorithms , Data , Data Science , Algorithms , Civic Technology , Technology, Civic , Diversity, Equity, Inclusion , Curriculum , Social Impact , Educational Opportunities
Project
Authors
Richter, Franscisca Garcia-Cobian
Date Submitted
7/1/23
Material Type
Collection
Secondary Material Type
Model
Institution
Case Western Reserve University
Industry Partner
License
CC BY-NC-SA
Funding Source
Network Challenge Grant TAACCCT Round 3
Additional Public Access
https://cwru-dsci.org/
Abstract
Development of key educational resources to integrate community knowledge into data science for social impact projects. The project has led to the development of a framework FAIR2 and resources to implement this framework. FAIR2 (Frame, Articulate, Identify, Report) guides data analysts in identifying and addressing discrimination bias in social data science. While the framework will be implemented by students enrolled in relevant classes at Case Western Reserve University, we are making all resources accessible through a newly created website to the general public: https://cwru-dsci.org/ We have built resources to illustrate how FAIR2 enriches data science with experiential knowledge,
clarifies assumptions about discrimination with causal graphs and systematically analyzes sources of bias in the data, leading to a more
ethical use of data and analytics for the public interest. FAIR2 can be applied in the classroom to prepare a new and diverse generation of
data scientists. The development of FAIR2 and accompanying resources was done through several steps that leveraged academic
and community partners, as planned in the proposal. Initially, we established a Community and Academic Advisory Group (CAAG) with
which we shared the aims of the project for feedback. We also established a process of community collaboration meetings or Data
Chats. Focusing on two data examples and inspired by Data Chats pioneered by Data You Can Use, we developed guides, IRB-approved
consent forms, and other materials for meetings with Subject Matter Experts, people whose experiences were represented in the data. We
are reporting on the insights from these meetings and how, through FAIR2, this knowledge guides data science for the public interest. A
paper on FAIR2 will be presented at the International Conference on Advanced Research Methods and Analytics in June 2023 and
published in the proceedings.
Industry (NAISC)
Public Interest Technology -- Data -- Algorithms
Occupation (SOC)
Computer and Mathematical Occupations -- Database Administrators (15-1061)
Instructional Program (CIP)
Social Sciences (45)
Credit Type
Credential Type
Certificate
Other
Other
Educational Level
Upper division of Bachelors degree or equivalent
Skill Level
Advanced Level