| Sponsored By: |
 |
Data vs. Information: Why We’re Here
By: Eliezer Israel
Information is one of the most valuable assets that an organization can have, but this information is often lost in mountains of data. In any large organization, there are hundreds of isolated data areas. Relational databases are each defined with their own structure and assumptions; legacy systems still carry echoes of punch card processing; communications standards are dictated without regard for the structure of the organization’s data. Data is duplicated, and duplicated again, as organizations fail to identify available resources. The amount of data explodes, as the quality of the data plummets.
Almost every organization has the data that it needs, somewhere. The problem is that the semantics of the data, the meaning of the data, that which makes it information, is known only locally. Globally, the meaning of the data is a mystery. Even when the meaning of a data area is discovered, it is often recorded only in a point-to-point mapping.
Organizations can realize great gains by using semantic methods of data management: by discovering the business meaning of their data, and recording that meaning in a mapping to a central model. What was previously a mystery can become a valuable asset. With a central model, an organization can have a single view of their data, and know what information is available.
These ideas are appearing in many different contexts – data quality efforts, applications engineering, web services discovery, message standard integration, and The Semantic Web. Standards are being set, and products are on the market, but until now there hasn’t been a central point for current information and discussion on semantic methods. That’s why we’re here.
Eliezer Israel is an information modeler and director of Semantic World. He
can be reached at Eliezer@SemanticWorld.Org.