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.
Authors
- Matthew S. Mayernik (ORCID: https://orcid.org/0000-0002-4122-0910)
Institutions
- NSF National Center for Atmospheric Research (US)
- University Corporation for Atmospheric Research (US)
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
Funders
- National Science Foundation