The second part, are the remaining tags in the yellow and green squares. These identify the fixed technical and business aspects of the data. The data remains the same regardless of the metadata naming conventions applied to it. The data object and thus the technical characteristics of the data object are the same.

The tags in the yellow square determine the physical components of the metadata, its structure, format, and value types. And the tags in the green box define the relational values of the metadata, the constraints on the use of the metadata, and the policies associated with the metadata. These are the key components of any data cleansing and the JUMP model provides a unified and concise view of this essential information.

An application that manages simple patient information will rely on a data model that maintains the patient's name. One application will track an individual's full name, while others will break up the name into its first, middle and last parts. And even those that track the given and family names of a patient will do it differently - perform a quick scan of the data sets within your own organization and you are likely to find 'LAST_NAME' attributes with a wide range of field lengths. For some data sets the patient name may be required, for others the patient ID may be required but the patient name may be optional. For some the name may require an address, but for others the name is related to the procedure in the application flow - and data relationships. JUMP presents a framework that makes analyzing the technical aspects of metadata for cleansing easier.