{"title":"Bringing information science perspectives to data science: Opportunities and gaps","authors":"Matthew S. Mayernik","doi":"10.1002/asi.25000","DOIUrl":null,"url":null,"abstract":"<p>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 <i>JASIST</i> 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.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 8","pages":"1047-1051"},"PeriodicalIF":4.3000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Association for Information Science and Technology","FirstCategoryId":"91","ListUrlMain":"https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.25000","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
The Journal of the Association for Information Science and Technology (JASIST) is a leading international forum for peer-reviewed research in information science. For more than half a century, JASIST has provided intellectual leadership by publishing original research that focuses on the production, discovery, recording, storage, representation, retrieval, presentation, manipulation, dissemination, use, and evaluation of information and on the tools and techniques associated with these processes.
The Journal welcomes rigorous work of an empirical, experimental, ethnographic, conceptual, historical, socio-technical, policy-analytic, or critical-theoretical nature. JASIST also commissions in-depth review articles (“Advances in Information Science”) and reviews of print and other media.
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