Data management procedures in ecological research

Ecological research requires a flexible, organized system for acquiring, documenting, and managing data. Careful documentation of data, best done through close collaboration of the researcher and data manager, is important if all users are to benefit from a centralized database management (DBM) system. A systematic approach to data management and analysis comprises four key steps: comprehension, planning, execution, and evaluation and interpretation. Statistical consulting at the beginning of a project helps scientists plan well-designed, efficient research strategies. Data collection forms should be designed to encourage recorders to enter all essential identifying information, therebyminimizing errors. Consistent, high-quality data verification, through either the visual or double-entry method, allows most data collection errors to be caught and corrected before analysis. Standardized forms help maintainuniformity in data documentation. Documentation and corresponding data files should be linked in a carefully organized relational DBM system in which all information may be easily stored and retrieved. Using commercial software for data management and analysis is usually more cost effective than developing and maintaining customized software. Scarce DBM resources should be invested in data validation, equipment acquisition, system design, and data documentation, not programming. Database maintenance is costly, but critical, to keeping credibility with users. The key to future advances in ecological data management lies in the ability of data managers and scientists to move into a more cooperative, integrative mode through which comprehensive databases are established and more fully used, increasing overall research efficiency.