Bringing information science perspectives to data science: Opportunities and gaps

Abstract Data science has many articulation points with information science, both in academic research contexts and in professional situations. Several recent journal special issues show the need for reflexivity in identifying and further building out these articulation points. In this brief communication, I outline aspects of data science that were not extensively discussed in detail within these special issues and deserve more attention from the JASIST community. I discuss how the information science community has important roles in building stronger theoretical understanding of data and data science, developing a more detailed understanding of the data science publishing landscape, and in mapping different manifestations of data science across societal sectors. Information science‐informed work in these areas will enable further understanding of data and data science as academic and societal phenomena.

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Institutions

Publication Details

Journal
Journal of the Association for Information Science and Technology
Published
2025-03-14
DOI
https://doi.org/10.1002/asi.25000
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28

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article

Bringing information science perspectives to data science: Opportunities and gaps

Matthew S. Mayernik
1 citations
Journal of the Association for Information Science and Technology
Big Data and Business Intelligence
2.28
article

Bringing information science perspectives to data science: Opportunities and gaps

Matthew S. Mayernik
article en
1 citations

Abstract

Abstract Data science has many articulation points with information science, both in academic research contexts and in professional situations. Several recent journal special issues show the need for reflexivity in identifying and further building out these articulation points. In this brief communication, I outline aspects of data science that were not extensively discussed in detail within these special issues and deserve more attention from the JASIST community. I discuss how the information science community has important roles in building stronger theoretical understanding of data and data science, developing a more detailed understanding of the data science publishing landscape, and in mapping different manifestations of data science across societal sectors. Information science‐informed work in these areas will enable further understanding of data and data science as academic and societal phenomena.

Journal of the Association for Information Science and TechnologyVol. 76(8)
NSF National Center for Atmospheric Research (US), University Corporation for Atmospheric Research (US)
National Science Foundation
Openalex Percentile: Top 14%
Big Data and Business Intelligence
2.28
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