“The classical approach to the data aspect of system design distinguishes conceptual, logical, and physical models. Models of each type or level are governed by metamodels that specify the kinds of concepts and constraints that can be used by each model; in most cases metamodels are accompanied by languages for describing models. For example, in database design, conceptual models usually conform to the Entity-Relationship (ER) metamodel (or some extension of it), the logical model maps ER models to relational tables and introduces normalization, and the physical model handles implementation issues such as possible denormalizations in the context of a particular database schema language. In this modeling methodology, there is a single hierarchy of models that rests on the assumption that one data model spans all modeling levels and applies to all the applications in some domain. The ‘one true model’ approach assumes homogeneity, but this does not work very well for the Web. The Web as a constantly growing ecosystem of heterogeneous data and services has challenged a number of practices and theories about the design of IT landscapes. Instead of being governed by ‘one true model’ used by everyone, the underlying assumption of top-down design, Web data and services evolve in an uncoordinated fashion. As a result, a fundamental challenge with Web data and services is matching and mapping local and often partial models that not only are different models of the same application domain, but also differ, implicitly or explicitly, in their associated metamodels.” (
Erik Wilde and
Robert J. Glushko)
