One nice thing about meta data is that it provides a level of abstraction regarding the description of data elements within a data set, and because of this, we also are able to abstract details of the instantiation of the data set. Conceptually, we can distinguish between the data elements along with their corresponding attributes and the formats in which sets of those data elements are collected, stored, exchanged, presented or grouped together. Consider an example using a simplistic meta data description of a customer:
Each data element is provided with a simple data type and size description. While this description does accurately provide information about a grouping of data elements, it does not specify whether we are talking about records in an RDBMS (relational database management system), rows in a flat file, a grouping of elements in an XML document, a row in a spreadsheet or any number of other possible materializations. However, any business rules that apply to the elements within a single instance, to a set of data instances, or to a set of these records compared to some other described data set, will still apply, regardless of what the actual physical representation is. This introduces an interesting question: If our business rules apply to the abstraction as described by the meta data, then can we abstract the application of business rules as well? I have discussed business rules as meta data in previous columns, but this month I am interested in a more basic question regarding data access: How do we manipulate data instances that may be represented in different ways? From a direct access approach, the problem is complex. From a programming point of view, however, using an object-oriented approach to develop an interface provides a way to mirror and consequently to exploit the meta data abstraction.
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