||Research Methods, Statistics, and Data/Data Analytics
||Organization of Information and Knowledge Management/Metadata
This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries.
Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice.
Partially due to how quickly data science evolves, libraries have yet to recognize core competencies and skills required to perform the job duties of a data librarian. As society transitions from the information age into the era of big data, librarians and information professionals require new knowledge and skills to stay current and take on new job roles, such as data librarianship. Skills such as data curation, research data management, statistical analysis, business analytics, visualization, smart city data, and learning analytics are relevant in library services today and will become increasingly so in the near future. This text serves as a tool for library and information science students and educators working on data science curriculum design.
- Reviews fundamental concepts and principles of data science
- Offers a practical overview of tools and software
- Highlights skills and services needed in the 21st-century academic library
- Covers the entire research data life cycle and the librarian's role at each stage
- Provides insight into how library science and data science intersect