Data Curation Competencies, Skill sets, and Tools Analysis
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Date
2024
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American English
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Springer
Abstract
The project aims to extend the current understanding of data curation competencies by examining existing skill sets and tools through a systematic analysis of data curation literature. For this research, the researchers reviewed forty-two data curation-related documents, including peer-reviewed literature, conference papers, and book sections through descriptive quantitative analysis and inductive qualitative content analysis based on a systematically created document protocol to extract informational items about the documents, as well as competencies, skills, and tools relevant to data curation activities. This paper presents the preliminary findings of this analysis and future steps for this project.
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Murillo, A. P., Yoon, A., Duncan, M., & Thomas-Fennelly, A. (2024). Data curation competencies, skill sets, and tools analysis. In: Sserwanga, I., et al. Wisdom, Well-Being, Win-Win. iConference 2024. Lecture Notes in Computer Science, vol 14596. Springer, Cham. https://doi.org/10.1007/978-3-031-57850-2_26
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This project is supported by the Institute of Museum and Library Services Grant # RE-252380-OLS-22.
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Conference paper