I am fascinated by the wide variety of database solutions in place across all industries that are referred to as data warehouses. It seems that any time data is placed in a database, whether from one source system or from multiple sources, it can be referred to as a data warehouse. In healthcare in particular, the concept of a replicated data store is a common occurrence (unfortunately, few actually call it this) – this is probably due to the complexity and depth of healthcare data in combination with the massive number of source systems. These complexities make true integration of data a significant challenge and providing a Replicated Data Store on one platform at least provides a one stop shop. Replicated data stores can be invaluable for any number of purposes, but they should definitely not be confused with a data warehouse. In this article we are going to investigate some of the characteristics and values of each of these architectural approaches.

The term “Intellectual Capital” collectively refers to all resources that determine the value of an organization, and the competitiveness of an enterprise. Understandably, the term “intellectual capital” from a human resources perspective is not easily translatable into financial terms. For all other assets of a company, there exists standard criteria for expressing their value. Perhaps, this term could more appropriately termed a “non-financial asset.” In an article written by Paolo Magrassi titled “Taxonomy of Intellectual Capital”, 2002, Mr. Magrassi defines human capital as “the knowledge and competencies residing with the company’s employees” and defines organizational intellectual capital as “the collective know-how, even beyond the capabilities of individual employees, that contributes to an organization.”

This is the third in a series of articles on the Semantic Web and EIM. Click here for the second installment. In this article I will discuss how the Semantic Web and semantic technologies can be used for meta data management and meta data analysis.