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Developing Categories of Data Reuse Patterns for the Medical Field

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Sustainability and Empowerment in the Context of Digital Libraries (ICADL 2024)

Abstract

This study focuses on the significant role played by reusing datasets in promoting open science. This study reported on the process of developing dataset reuse pattern categories and verified that these categories could be used to identify the role of reusing datasets. Articles that cited the biomedical dataset of the Framingham Cohort were included in the sample. Two annotators assigned categories to the samples by checking titles, journal names, author information, purpose, description of the dataset, and statements of data in the body of the articles; 11 categories were identified. The analysis of the sample articles with assigned categories indicated that this category set can contribute to verifying the increasing diversity of reuse patterns, expanding research areas, and contributing to data-driven research by reusing data. This study serves as a testament to the advantages of data reuse and inspires researchers to consider the impacts of data sharing practices.

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Acknowledgments

This work was supported by JSPS KAKENHI Grant Number JP24K03229.

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Correspondence to Emi Ishita .

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Ishita, E., Miyata, Y., Kurata, K. (2025). Developing Categories of Data Reuse Patterns for the Medical Field. In: Oliver, G., Frings-Hessami, V., Du, J.T., Tezuka, T. (eds) Sustainability and Empowerment in the Context of Digital Libraries. ICADL 2024. Lecture Notes in Computer Science, vol 15494. Springer, Singapore. https://doi.org/10.1007/978-981-96-0868-3_22

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  • DOI: https://doi.org/10.1007/978-981-96-0868-3_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-96-0867-6

  • Online ISBN: 978-981-96-0868-3

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