Data Science in Libraries: Findings and a Roadmap Forward


Summary

The video discusses the importance of obtaining IMLS funding to train librarians in data science, addressing challenges in data manipulation and management faced by libraries. It emphasizes the need for data science training initiatives like Data Scientist Librarians at NC State and the Australian National Data Service to bridge gaps in skills and resources. The talk also delves into the role of libraries in data management, promoting data literacy, and navigating ethical concerns with complex data sets, while highlighting the roadmap for future workshops to enhance data science education in libraries.


Introduction and Funding

Discussion on the desire to obtain IMLS funding for specific individuals involved in the study to train librarians and expose them to data science.

Workshop Overview

Explanation of the workshop structure and focus on the National Digital Platform, data manipulation, analysis, and management challenges faced by librarians.

Challenges Faced by Librarians

Addressing the gaps in data science training, management practices, and the need to employ data science in libraries.

Training Initiatives

Highlighting major training initiatives for librarians such as Data Scientist Librarians at NC State and the Australian National Data Service.

Key Insights from Workshop

Discussing the key findings and facets identified during the workshop, including organizational structures, skills training, and library resources.

Role of Libraries

Exploring the role of libraries in data management, promoting data literacy, and supporting research projects.

Barriers and Concerns

Addressing barriers related to formal LIS education, incentive structures, resource allocation, leadership challenges, and scalability of data science services in libraries.

Ethical Considerations

Highlighting ethical questions and the role of research librarians in navigating new and complex data sets with potential risks and ethical concerns.

Future Directions

Discussing the roadmap development, stakeholder involvement, and plans for convening workshops to showcase data science projects and improve data science education discovery.

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