Types of domain and task‐solving information in media scholars' data interaction
Laura Korkeamäki,
Heikki Keskustalo and
Sanna Kumpulainen
Journal of the Association for Information Science & Technology, 2024, vol. 75, issue 4, 454-468
Abstract:
The purpose of this study is to examine what types of domain and task‐solving information media scholars need while interacting with research data to create new knowledge. The study is situated within information interaction research in information science. The approach is user‐oriented and qualitative. The research data consist of interviews of 25 media scholars about their interactions with research data. In the analysis, deductive and inductive approaches were combined to identify domain and task‐solving information types from the interview data. The results show that media scholars needed two domain information types and three task‐solving information types while interacting with research data. The domain information types were (1) earlier research information and (2) experience‐based domain information. The task‐solving information types were (1) information about methods and tools, (2) information about rules and norms, and (3) self‐created task‐supporting information. Of these, experience‐based domain information and self‐created task‐supporting information have been less considered in prior research on domain and task‐solving information. The findings of this study are useful for providing support for data interaction. Furthermore, the study sheds light on the concepts of domain information and task‐solving information in the context of interacting with research data.
Date: 2024
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https://doi.org/10.1002/asi.24863
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:75:y:2024:i:4:p:454-468
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