Technological advances and the rise of collaborative, interdisciplinary approaches have changed the practice of research. The 21st century researcher not only faces the challenge of managing increasingly complex datasets, but also new data sharing requirements from funders and journals. Success in today's research enterprise requires an understanding of how to work effectively with data, yet most researchers have never had any formal training in data management. Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise,…mehr
Technological advances and the rise of collaborative, interdisciplinary approaches have changed the practice of research. The 21st century researcher not only faces the challenge of managing increasingly complex datasets, but also new data sharing requirements from funders and journals. Success in today's research enterprise requires an understanding of how to work effectively with data, yet most researchers have never had any formal training in data management. Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise, giving librarians exciting new opportunities to use their expertise and skills. The Medical Library Association Guide to Data Management for Librarians highlights the many ways that librarians are addressing researchers' changing needs at a variety of institutions, including academic, hospital, and government libraries. Each chapter ends with "pearls of wisdom," a bulleted list of 5-10 takeaway messages from the chapter that will help readers quickly put the ideas from the chapter into practice. From theoretical foundations to practical applications, this book provides a background for librarians who are new to data management as well as new ideas and approaches for experienced data librarians.
Lisa M. Federer is Research Data Informationist at the National Institutes of Health (NIH) Library, where she provides training and support in the management, organization, and re-use of biomedical research data for researchers in the NIH's Intramural Research Program. She received her Masters of Library and Information Studies from the University of California, Los Angeles in 2011 and also holds an MA in English. She has also completed graduate certifications in data visualization from New York University and data science from Georgetown University.
Inhaltsangabe
Part One: Theory and Foundations Chapter 1. Data Management: Theory and Foundations Chapter 2. Research Data Management for the Digital Research Enterprise: A Perspective from the National Institutes of Health Valerie Florance Chapter 3. What Could Possibly Go Wrong? The Impact of Poor Data Management Chris Eaker Chapter 4. Research Data as Record Bethany Myers Chapter 5. Raising Researchers' Awareness of Biomedical Data Journals to Promote Data Sharing Katherine G. Akers Chapter 6. Data Science: New Librarian Roles for a New Field of Research Lisa M. Federer Chapter 7. Data 101: Learning and Keeping Current in Data Management Skills Abigail Goben and Rebecca Raszewski Part Two: Data Management Across the Research Data Life Cycle Chapter 8. Data Management Across the Research Data Life Cycle Chapter 9. Library Support for Data Management Plans Carrie Iwema, Melissa Ratajeski, and Andrea Ketchum Chapter 10. Going Beyond the Data Management Plan Lisa Zilinski, Abigail Goben, and Kristen Briney Chapter 11. Library Infrastructures for Scholarship at Scale Steven Braun Chapter 12. Contextualizing Visualization in Library Services Marci Brandenburg and Justin Joque Part Three: Data Management in Practice Chapter 13 Data Management in Practice Chapter 14. Data Services at a Medium-Sized Academic Library Bonnie L. Fong, Minglu Wang, and Ann Vreeland Watkins Chapter 15. Data Information Literacy: Engaging with the Undergraduate Health Sciences Population Yasmeen Shorish and Carolyn Schubert Chapter 16. Building Data Management Services at an Academic Medical Center: An Entrepreneurial Approach Alisa Surkis and Kevin Read Chapter 17. Data Management in the Lab Caitlin Bakker Chapter 18. Demystifying Data Management: Designing Services for Hospital-based Researchers Jeannine Cyr Gluck
Part One: Theory and Foundations Chapter 1. Data Management: Theory and Foundations Chapter 2. Research Data Management for the Digital Research Enterprise: A Perspective from the National Institutes of Health Valerie Florance Chapter 3. What Could Possibly Go Wrong? The Impact of Poor Data Management Chris Eaker Chapter 4. Research Data as Record Bethany Myers Chapter 5. Raising Researchers' Awareness of Biomedical Data Journals to Promote Data Sharing Katherine G. Akers Chapter 6. Data Science: New Librarian Roles for a New Field of Research Lisa M. Federer Chapter 7. Data 101: Learning and Keeping Current in Data Management Skills Abigail Goben and Rebecca Raszewski Part Two: Data Management Across the Research Data Life Cycle Chapter 8. Data Management Across the Research Data Life Cycle Chapter 9. Library Support for Data Management Plans Carrie Iwema, Melissa Ratajeski, and Andrea Ketchum Chapter 10. Going Beyond the Data Management Plan Lisa Zilinski, Abigail Goben, and Kristen Briney Chapter 11. Library Infrastructures for Scholarship at Scale Steven Braun Chapter 12. Contextualizing Visualization in Library Services Marci Brandenburg and Justin Joque Part Three: Data Management in Practice Chapter 13 Data Management in Practice Chapter 14. Data Services at a Medium-Sized Academic Library Bonnie L. Fong, Minglu Wang, and Ann Vreeland Watkins Chapter 15. Data Information Literacy: Engaging with the Undergraduate Health Sciences Population Yasmeen Shorish and Carolyn Schubert Chapter 16. Building Data Management Services at an Academic Medical Center: An Entrepreneurial Approach Alisa Surkis and Kevin Read Chapter 17. Data Management in the Lab Caitlin Bakker Chapter 18. Demystifying Data Management: Designing Services for Hospital-based Researchers Jeannine Cyr Gluck
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