In pathology, computerized data management systems have been used increasingly to facilitate a more efficient supply of information. Since data entry precedes data utilization, the reliability of the information stored strongly depends on the quality of data input. Despite its potential capability, most personal computer-based database software does not provide versatile and user-friendly data validation procedures. Therefore, we developed a data dictionary-driven data management system that enables the user to perform extensive validation routines without the need for hard programming. Using examples from an existing database for endometrial carcinomas, different types of data errors and their error traps are explained. It is pointed out that data type definitions, defaults, templates, or picture clauses are suitable means to avoid formal errors. Validations on data domains and ranges test whether data fall into a predefined scope. Relational checks control data validity within a context of different data items, whereas process routines provide automatic data computation, thereby circumventing user input. By exploiting the facilities of an extended data dictionary, a powerful tool is made available to secure various aspects of data integrity simultaneously with input. In this way, computerized data quality control can improve the efficiency and reliability of data management tasks in pathology.