Nina (who still does not seem to blog) wrote up this interesting question, triggered by the OpenTox API ontology:

Given: A publication, describing specific method of property prediction (not a generic machine learning algorithm). An implementation of this publication.

Example: pKa. This is a decision tree with SMARTS in the nodes. There is a training set, which could be used in validation.

  • Should it be exposed by OpenTox services as ot:Algorithm or ot:Model ?
  • What is the right way to use / extend Blue Obelisk descriptors dictionary to describe this implementation?
  • Would you classify this method as a descriptor calculation or as a predictive model?

I would say, a ot:Model is a ot:Algorithm, just a comlex one.

The question shows one of the virtues of ontologies: they require us to carefully think about what we say. It is almost as like they put the scholar back into science.

On a different note, can we please start making an Open Data pKa database?!?

This post was originally posted as https://chem-bla-ics.blogspot.com/2010/10/algorithm-or-model-opentox-api-quiz.html.