Principles of artificial intelligence
Principles of artificial intelligence
Recording the reasons for design decisions
ICSE '88 Proceedings of the 10th international conference on Software engineering
F-logic: a higher-order language for reasoning about objects, inheritance, and scheme
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Extending the Potts and Bruns model for recording design rationale
ICSE '91 Proceedings of the 13th international conference on Software engineering
The unified software development process
The unified software development process
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
Design Rationale Systems: Understanding the Issues
IEEE Expert: Intelligent Systems and Their Applications
Creating Semantic Web Contents with Protégé-2000
IEEE Intelligent Systems
Questions, options, and criteria: elements of design space analysis
Human-Computer Interaction
Human-Computer Interaction
Design rationale: Researching under uncertainty
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
| Hi-index | 0.00 |
This paper presents the Kuaba Ontology, a knowledge representation model for Design Rationale described in an ontology definition language. The representation of this model in a specific ontologies specification language, such as OWL or F-Logic, allows attributing semantics to recorded Design Rationale content, and defining rules that enable performing computable operations to support the use of Design Rationale in the design process of new artifacts. In addition, we propose to support the software design process through the use of the semantic descriptions defined by formal models of the artifacts. Representing Design Rationale using an ontology definition language and the artifacts formal model, enables a type of software reuse at the highest abstraction level, where rationales are re-employed in designing a new artifact. This kind of reuse is possible in knowledge domains where there are formal models describing the artifacts, in particular, in the Software Design domain.