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Data Science Education in Library and Information Science Schools

机译:图书馆与信息科学学院的数据科学教育

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摘要

The need for data science education has grown recently among Library and Information Science schools to better prepare information professionals for the world of big data. However, there are many challenges to providing education on data science in Library and Information Science schools. For example, developing curricula and models for managing faculty resources (full-time teaching, buy-out, or specialized faculty) are some initial, common challenges. Participants will present their experiences and insights regarding data science education, which may include curricula, barriers, and best practices in the panel presentations. The panel session then will open up to an active discussion session with the audience, who will be encouraged to share their experiences and insights. This panel session is part of an ongoing effort by the organizers to establish sustainable data science education in Information Science schools. Developing a framework and curricula of data science education in Information Science schools, based on best practices and informed by experience, is the optimal goal of this ongoing effort. The success of this effort depends on active participation of the participants. This panel is sponsored by SIG ED.
机译:最近对图书馆和信息科学学校的数据进行增长的需求,以更好地为大数据世界编写信息专业人士。但是,在图书馆和信息科学学校提供数据科学教育存在许多挑战。例如,制定管理教师资源(全日制教学,买入或专业教师)的发展课程和模型是一些初始,共同的挑战。参与者将展示他们的经验和有关数据科学教育的见解,这可能包括小组介绍中的课程,障碍和最佳实践。然后,小组会议将与观众开放积极的讨论会,将鼓励谁分享他们的经验和见解。本小组会议是组织者在信息科学学校建立可持续数据科学教育的持续努力的一部分。基于最佳实践和经验告知,制定信息科学学校数据科学教育的框架和课程,是这种持续努力的最佳目标。这项努力的成功取决于参与者的积极参与。本面板由SIG ED赞助。

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