In recent years, ontology-driven applications gained more and more
momentum by smartening functionalities ranging from inferencing to
querying and data integration. Nowadays, ontology-driven applications
are finding their way also into traditional application domains.
Development environments for constructing the core, i.e., the semantic
infrastructure, of those ontology-driven applications suffer from three
crucial deficiencies. First, inadequate abstraction mechanisms force
software engineers to deal with intricacies of underlying semantic
technologies. Second, change-agnostic editors neglect the importance and
meaning of changes by dealing with semantic infrastructures as editable
semantic artifacts only. Third, limited co-evolution support of highly
interdependent semantic artifacts hamper maintenance of infrastructures
evolving together with the applications. This leads to increased
development times, decreased software quality and consequently, impedes
efficient adoption of semantic technologies for smartening applications.
DARWIN proposes a novel extensible framework to develop and maintain
semantic infrastructures based on model engineering techniques. The
innovations are manifested in three key research goals. First, DARWIN
aims at tailoring existing conceptual modeling languages allowing to
model semantic infrastructures on a technology-independent abstraction
layer and to automatically generate technology-specific implementations.
Second, DARWIN focuses on precisely tracking evolution at modeling
level, being the pre-requisite for incremental change propagation to the
implementation level. Third, DARWIN targets semi-automatic co-evolution
of interdependent semantic artifacts to enhance maintainability while
ensuring global consistency. Solutions are realized by means of a
prototype and will be integrated for demonstration purposes within the
commercial UML tool Enterprise Architect.
Forschungs-