Principles of research data collection and management is the first practical book written for researchers and research team members covering the dos and donts about handling data for research. The book covers basic types of data and fundamentals of how data grow, move and change over time. Focusing on pre-publication data collection and handling, the text illustrates use of these key concepts to match data collection and management methods to a particular study, in essence, making good decisions about data.
The first section of the book defines data, introduces fundamental types of data that bear on methodology to collect and manage them, and covers data management planning and research reproducibility. The second section covers basic principles of and options for data collection and processing emphasizing error resistance and traceability. The third section focuses on managing the data collection and processing stages of research such that quality is consistent and ultimately capable of supporting conclusions drawn from data. The final section of the book covers principles of data security, sharing and archival. This book will help graduate students and researchers systematically identify and implement appropriate data collection and handling methods.
Dr. Zozus has spent over two decades managing data for research and studying methodology for doing so. She has worked in data management for life sciences, engineering and biomedical research. She received her undergraduate and masers degrees in Nuclear Engineering at North Carolina State University, led data management operations at the Duke Clinical Research Institute and later the Duke Translational Medicine Institute. Dr. Zozus received her PhD in Health Informatics at the University of Texas at Houston School of Biomedical Informatics.
Chapter 1: Collecting and Managing Research Data
Part 1: Planning for Data Collection and Management
Chapter 2: Defining Data and Information
Chapter 3: Deciding What Data to Collect, Defining and Documenting It
Chapter 4: Reproducibility, Data management plans and Data management documentation
Part 2: Data Observation, Recording and Processing
Chapter 5: Timing of Observation, Recording and Processing
Chapter 6: Data Observation and Recording
Chapter 7: Good Documentation Practices Applicable to Man and Machine
Chapter 8: Getting Data Into Electronic Format
Chapter 9: Data Structures
Chapter 10: Data Processing
Part 3: Managing Data Management
Chapter 11: Designing and Documenting Data flow and Workflow
Chapter 12: Selecting Software for Collecting and Managing Data
Chapter 13: Data Management Quality System
Chapter 14: Calculating the Time and Cost for Data Collection and Processing
Part 4: Data Security, Sharing and Archival
Chapter 15: Research Data security
Chapter 16: Data Ownership, Stewardship and Sharing
Chapter 17: Data Archival
Glossary
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