Book Description

To expedite the research data management system (RDMS) required for complex and large-scale ecological field studies being done at the U.S. Army Engineer Waterways Experiment Station (WES), a graphical display system was developed. The Statistical Analysis System (SAS) provides the framework for making open-ended RDMS practical and cost-effective. PROC VIVIPLOT is the first of a series of SAS procedures that will produce copy-ready figures with some independence as to choice of plotter. Several approaches are available that minimize errors in coding variables. Numeric codes, 'smart codes, ' with embedded information allocated to positions within the value codes are widely used but unacceptable for variables with many values and/or many levels of classification. 'Nonsense' codes, or codes without embedded information, however, efficiently circumvent the problems associated with smart codes. Using nonsense codes, alphanumeric variable values are assigned a sequential numeric code as new values are encountered in the data base, irrespective of the position of the value in the classification scheme for that variable. With the use of nonsense codes, the management approach is open-ended and does not require a knowledge of the number of potential classification levels for the variables. In addition, experience with several large environmental data bases indicates that coding errors appear to be less frequent using nonsense codes than in those studies in which a smart code approach was used.