Data Science Education in Library and Information Science Schools

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Abstract
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.

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