ABSTRACT
In any research project, no matter how many people are involved, the researcher is ultimately responsible for the ability of the data to support research conclusions. This book presents methods that produce reliable and accurate data; however, the infrastructure and environment in which these methods are applied also have bearing on the outcome. Quality management theory and practice also take this holistic perspective. This chapter combines theory and approaches in quality management and applies them specifically to the challenge of managing data in research settings to define a data management quality system.
