Many data modelers divide the world into data and metadata. Metadata is data about data. These objects are called metadata because they are one step removed from the data. Domains A domain is the set of possible values an attribute type can have. Domains are important because they tell you not only what the acceptable values of an attribute are, but also how to use the attribute.
Domains can be specific or generic.
Generic domains, such as 'integer,' 'text,' or the ever-popular 'alphanumeric,' are the easiest to work with, but they're also the least meaningful. Acceptable Values , such as Zip codes, State names, and U.S. Presidents, are the most specific types of domains. They specify the only values an attribute can have. In effect, a domain hierarchy is created with the data type at the highest level and acceptable values at the lowest. The ER approach to logical data modeling does not end here.