Big ideas, small data

Opportunities and challenges for data science and the social services sector

Bibliographic Data

ID5260736
AuthorsGeri Louise Dimas (0000-0002-7934-5436, Worcester Polytechnic Institute, corresponding author), Lauri Goldkind (0000-0002-0967-3960, Fordham University), Renata Konrad (0000-0002-6015-9203, Worcester Polytechnic Institute)
Year2023
Volume10
Issue1
Publication date2023-01-01
Open AccessYes
TypeARTICLE
VenueBig Data & Society (JOURNAL)
Journal identifiersISSN: 2053-9517 • E-ISSN: 2053-9517
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/20539517231171051
OpenAlexW4368276051
LanguageEN
Citations received5
References cited16

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 accompanied 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 scientists interested in working within the social services sector can enhance their contributions to the field: refining and leveraging available data, improving collaborations, and respecting data limitations

Big data · Business · Crowdsourcing · Data as a service · Data mining · Data quality · Data science · Knowledge management · World Wide Web · Computer Science · Ethics in Clinical Research · Geriatric Care and Nursing Homes · Health Policy Implementation Science · Marketing

Tools

Open DOIOpen Access