Excerpts from Nina Jeliazkova's message of Fri Aug 20 23:07:22 +0200 2010:

> My fault for not being clear - the superservice will not build a
> model,  it could only apply a model.  To build a model, just POST the
> dataset and prediction feature to the algorithm uri directly.

Ok, lets see if I understand correctly:

To create a prediction model from scratch I would have to

- create a dataset with structures and activities
- calculate (and eventually select) descriptors using one of the feature
  calculation (selection) algorithms
- apply one of the modelling algorithms to create a prediction model 

To make predictions I would use the superservice:

- create a dataset with structures to be predicted
- submit the prediction dataset and the model to the superservice to
  obtain a dataset with the predictions

Is this correct?

To simplify this procedure we are using for our services the following convenience methods:

Model creation:

  curl -X POST -d dataset_uri={datset_uri} -d feature_uri={feature_uri} -d feature_generation_uri={feature_generation_uri} {model_algorithm_uri}
  returns task URI for the prediction model, feaure_uri specifies the dependent variable
  - calls feature_generation_algorithm for dataset
  - creates prediction model from calculated descriptors and training
    activities (in dataset)

I think this schema is rather generic as it allows to combine arbitrary modelling algorithms with any supervised and unsupervised feature generation algorithms. Additional parameters for modelling/feature generation algorithms will be forwarded to these services.

Predictions:

Predict a dataset (seems to be similar to superservice, but is included in the model service)

  curl -X POST -d dataset_uri={dataset_uri} {model_uri}
  returns task URI for prediction dataset
  - calls feature_generation_algorithm for dataset
  - uses model to create a prediction dataset

Predict a compound (convenience method without storing a dataset)

  curl -X POST -d compound_uri={compound_uri} {model_uri}
  returns prediction as rdf/xml or yaml
  - calls feature_generation_algorithm for compound
  - uses model to create a prediction for compound

Do you think we should unify? I would like to keep our methods, because
I find them intuitive and handy, but can of course provide a
superservice like interface.

Best regards,
Christoph