Abstract
Data have integrity when they are free of data abnormalities and data manipulations. Maintaining data integrity is a responsibility of all those involved in research, not only data managers. The costs of data integrity problems and of responding to them when they are discovered can be high; therefore, prevention of data integrity problems is far better than correcting them after they have been made. However, even when good strategies are employed to prevent data integrity problems (a topic discussed previously), it is inevitable that some data integrity problems will occur. The specific foci of this chapter are thus on (1) operational problems occurring in spite of detailed quality assurance and data management plans and (2) adaptive responses. Some data integrity challenges and possible solutions in resource-limited settings are also highlighted.
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