Document Type
Article
Keywords
big data, social services, human services, small data, data science
Disciplines
Data Storage Systems | Nonprofit Studies | Social Justice | Social Work
Abstract
The social services sector, comprised of a constellation of programs meeting critical human needs, lacks the resources and infrastructure to implement data science tools. As the use of data science continues to expand, it has been accom- panied by a rise in interest and commitment to using these tools for social good. This commentary examines overlooked, and under-researched limitations of data science applications in the social sector—the volume, quality, and context of the available data that currently exists in social service systems require unique considerations. We explore how the presence of small data within the social service contexts can result in extrapolation; if not properly considered, data science can negatively impact the organizations data scientists are trying to assist. We conclude by proposing three ways data scien- tists interested in working within the social services sector can enhance their contributions to the field: refining and lever- aging available data, improving collaborations, and respecting data limitations.
Publication Title
Big Data & Society
Article Number
1042
Publication Date
2023
DOI of Published Version
20539517231171051
Language
English
Peer Reviewed
1
Recommended Citation
Dimas, G. L., Goldkind, L., & Konrad, R. (2023). Big ideas, small data: Opportunities and challenges for data science and the social services sector. Big Data & Society, 10(1), 20539517231171051.
Link to request form
1
Version
Published
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Included in
Data Storage Systems Commons, Nonprofit Studies Commons, Social Justice Commons, Social Work Commons
