Technical data standards abound in many
industries. Bringing data together from across these standards is often
challenging. This is because they're technical standards – they don't have a
business meaning. You need to add this missing layer in the form of a common
business model or what's sometimes called semantic data. In other words, you've
got to overlay meaning on the data.
But people can find it hard to agree on meanings because they come at data with different uses in mind. You will approach data differently if you're concerned with providing management information than if you're looking to connect business partners. The ability to abstract yourself away from your own immediate purposes and see the other guy's point of view is central to making progress with a common model. More importantly, this is the same ability that lies at the heart of successful knowledge-based organizations. We live in an era when connecting with others and sharing information are more important than defending home territory.
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