Identifying the Complex Position of Research Data and Data Sharing Among Researchers in Natural Science
Keiko Kurata, Mamiko Matsubayashi, Shinji Mine
Abstract
Open-access reader
Keiko Kurata, Mamiko Matsubayashi, Shinji Mine
Abstract
Open-access reader
This article aims to provide an overview of researchers’ practices and perceptions on data use and sharing. Semistructured interviews were conducted with 23 Japanese researchers in the natural sciences to identify their research practices and data use, including data sharing. We divided the interview scripts into meaningful phrases as a unit of analysis. Next, we focused on 406 statements on research data and reanalyzed them based on four aspects: stance on research data, practices and perceptions of data use, range of data sharing, and data type. A cluster analysis identified 14 clusters, which were divided into five groups: open access for data, restricted access for data, data interpretation, data processing and preservation, and data infrastructure. Our results reveal the complexity and diversity of the relationship between data and research practices. That is, the practice of research data sharing is heterogeneous, with no “one size fits all” between and among researchers.
OpenAlex reports 24 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This article aims to provide an overview of researchers’ practices and perceptions on data use and sharing. Semistructured interviews were conducted with 23 Japanese researchers in the natural sciences to identify their research practices and data use, including data sharing. We divided the interview scripts into meaningful phrases as a unit of analysis. Next, we focused on 406 statements on research data and reanalyzed them based on four aspects: stance on research data, practices and perceptions of data use, range of data sharing, and data type. A cluster analysis identified 14 clusters, which were divided into five groups: open access for data, restricted access for data, data interpretation, data processing and preservation, and data infrastructure. Our results reveal the complexity and diversity of the relationship between data and research practices. That is, the practice of research data sharing is heterogeneous, with no “one size fits all” between and among researchers.
Key concepts: Data sharing, Data science, Computer science, Data type, Scripting language, Open data, World Wide Web, Programming language