They were data that helped people understand and manage their data resource so that it could be fully utilized to support the organization’s current and future business information demand. Meta-data traditionally represented data names, data definitions, data structure, data edits, and so on. The first common misperception is the difference between meta-data and business data. It’s those errors that are seriously impacting formal data resource management. The term meta-data has become quite meaningless and has led to numerous misconceptions about what meta-data represent and how they are used. If a group of people were asked to define meta-data, there would be as many different definitions as there were people in the group. That definition is neither comprehensive nor denotative and can be interpreted in many different ways through individual connotative interpretations. The term meta-data has typically been defined as data about data, which is a tautology. The confusion about a concept as important as understanding the meaning of all the data in an organization’s data resource leads to increased data disparity and low quality data that do not fully meet an organization’s current and future business information demand. These terms are an excellent example of the huge lexical challenge that data resource management faces today. The terms meta-data and metadata have been used, misused, and abused to the point that the real meaning is totally unclear and may even be unknown.
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