Hard Problems in Schema Mapping

• Onto mappings
  Example: Numeric grades to letter grades [give credit to the H.P. paper]
• Different categorizations
  I.e., Data model A records (Unit color, Number sold), and data model B records (Unit weight, Number sold). Unless color => weight or weight => color, there's a serious limit on any unified data model that wants to represent Number units sold in a useful way.
• Recognizing object identity
  Problem: Each schema implies that is only has one data object per object in the modeled system. When producing a unified database, it's possible to lost this one-data-object-per-modeled-object quality unless care is taken. Even then, it can be a hard problem to solve (** Research this better - cjc).
• Conflicting data
  Schema semantics often make an implicit claim that data using the schema is absolutely correct. People usually know to take that claim with a grain of salt. When unifying data from two or more data sources, contradictions can be reached, leading to an internally inconsistent view of data.
• Unequal expressive power of schemas
  By way of example, object-oriented databases (OODBs) might include their method behaviors as part of the schema. However, SQL schemas have only limited support for expressing system behavior.

  In particular, the OODB methods might be written in computationally complete languages, and SQL is not computationally complete. The important lesson from this is that care must be taken in the selection of which schema type to use for presenting the integrated view of the data.