The Units Ontology makes reference to the Gene Ontology as an example of a successful web ontology effort.
As it should. The Gene Ontology (GO) is the only successful web ontology effort. A universe with one (1) inhabitant.
The GO has a number of differences from wannabe successful ontology candidates. (see the article below)
The first difference echoes loudly across the semantic engineering universe:
One of the factors that account for GO’s success is that it originated from within the biological community rather than being created and subsequently imposed by external knowledge engineers. Terms were created by those who had expertise in the domain, thus avoiding the huge effort that would have been required for a computer scientist to learn and organize large amounts of biological functional information. This also led to general acceptance of the terminology and its organization within the community. This is not to say that there have been no disagreements among biologists over the conceptualization, and there is of course a protocol for arriving at a consensus when there is such a disagreement. However, a model of a domain is more likely to conform to the shared view of a community if the modelers are within or at least consult to a large degree with members of that community.
Did you catch that first line?
One of the factors that account for GO’s success is that it originated from within the biological community rather than being created and subsequently imposed by external knowledge engineers.
Saying the “O” word, ontology, that will benefit everyone if they will just listen to you, isn’t enough.
There are other factors to consider:
A Short Study on the Success of the Gene Ontology by Michael Bada, Robert Stevens, Carole Goble, Yolanda Gil, Michael Ashburner, Judith A. Blake, J. Michael Cherry, Midori Harris, Suzanna Lewis.
Abstract:
While most ontologies have been used only by the groups who created them and for their initially defined purposes, the Gene Ontology (GO), an evolving structured controlled vocabulary of nearly 16,000 terms in the domain of biological functionality, has been widely used for annotation of biological-database entries and in biomedical research. As a set of learned lessons offered to other ontology developers, we list and briefly discuss the characteristics of GO that we believe are most responsible for its success: community involvement; clear goals; limited scope; simple, intuitive structure; continuous evolution; active curation; and early use.