Abstract: The techniques described herein automatically and programmatically harmonize data, and map variable names from a dataset to standards of domains for data in the dataset. Each variable may be stored in a table which holds related groups of variables. The variables may be named by defining mappings, each mapping including two mapping rules. A first mapping rule maps a domain of the standard to the table, while a second mapping rule maps a variable within the table to a variable within the domain. When a mapping rule exists that provides an exact match between a variable name and a standard, an auto-mapping feature may be applied that automatically maps the variable name to the standard. If no exact match exists, then an analysis is performed to determine the most likely mapping candidate.

Abstract: The techniques described herein automatically and programmatically harmonize data, and map variable names from a dataset to standards of domains for data in the dataset. Each variable may be stored in a table which holds related groups of variables. The variables may be named by defining mappings, each mapping including two mapping rules. A first mapping rule maps a domain of the standard to the table, while a second mapping rule maps a variable within the table to a variable within the domain. When a mapping rule exists that provides an exact match between a variable name and a standard, an auto-mapping feature may be applied that automatically maps the variable name to the standard. If no exact match exists, then an analysis is performed to determine the most likely mapping candidate.