When modeling a complex system, you should always strive to design
a model that is as simple as possible. There are a number of signs that tell the ontologist that her classification is
just too complex.
1. Nobody, even the designers, fully understands the ontology model.
2. You realize that the ontology makes no sense. The solutions obtained by data analysts are
impossible, or they contradict observations. Tinkering with the ontology doesn’t help matters.
3. For a given problem, no two data analysts seem able to formulate the query the same way, and no
two query results are ever equivalent.
4. The ontology lacks modularity. It is impossible to remove a set of classes within the ontology
without collapsing its structure. When anything goes wrong, the entire ontology must be fixed or
redesigned, from scratch.
5. The ontology cannot fit under a higher level ontology or over a lower-level ontology.
6. The ontology cannot be debugged when errors are detected.
7. Errors occur without anyone knowing that the error has occurred.
8. You realize, to your horror, that your ontology has violated the cardinal rule of data simplification,
by increasing the complexity of your data.
The practical ontologist may need to
settle for a simplified approximation of the truth.
-Jules Berman (copyrighted material)
key words: ontology, classification, data simplification, jules j berman
