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  • × author_ss:"Bossaller, J."
  • × year_i:[2020 TO 2030}
  1. Bossaller, J.; Million, A.J.: ¬The research data life cycle, legacy data, and dilemmas in research data management (2023) 0.00 
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    Abstract
    This paper presents findings from an interview study of research data managers in academic data archives. Our study examined policies and professional autonomy with a focus on dilemmas encountered in everyday work by data managers. We found that dilemmas arose at every stage of the research data lifecycle, and legacy data presents particularly vexing challenges. The iFields' emphasis on knowledge organization and representation provides insight into how data, used by scientists, are used to create knowledge. The iFields' disciplinary emphasis also encompasses the sociotechnical complexity of dilemmas that we found arise in research data management. Therefore, we posit that iSchools are positioned to contribute to data science education by teaching about ethics and infrastructure used to collect, organize, and disseminate data through problem-based learning.
  2. Moulaison-Sandy, H.; Adkins, D.; Bossaller, J.; Cho, H.: ¬An automated approach to describing fiction : a methodology to use book reviews to identify affect (2021) 0.00 
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    Abstract
    Subject headings and genre terms are notoriously difficult to apply, yet are important for fiction. The current project functions as a proof of concept, using a text-mining methodology to identify affective information (emotion and tone) about fiction titles from professional book reviews as a potential first step in automating the subject analysis process. Findings are presented and discussed, comparing results to the range of aboutness and isness information in library cataloging records. The methodology is likewise presented, and how future work might expand on the current project to enhance catalog records through text-mining is explored.

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