Obtaining service compositions using WSMO from feature models

Our paper From Feature Models to Business Processes has been cited in a paper from SPLC 09. Concretely in the paper titled:

Semantic Variability Modeling for Multi-staged Service Composition. Bardia Mohabbati, Nima Kaviani and Dragan Gasevic.

The main goal of this work is to show how transformation of feature models to ontologies coupled with constraints over configuring products can help with reasoning over a product family and creating adaptive service compositions.

For that purpose, authors provide a complete description of service compositions using WSMO, from a previous feature model that describes configuration. This transformation is done by following the mapping rules between the feature models and abstract state machines defined in our work.

A copy of this paper is available in the website of Nima Kaviani.