Description
This contribution introduces the concept of Situational Reference Model Mining, i.e. the idea that automatically derived reference models, although based on the same input data, are intended for different use cases and thus have to meet different requirements. These requirements determine the reference model character and thus the technique that is best suited for mining it. Situational Reference Model Mining is based on well-known design principles for reference modeling, such as configuration, aggregation, specialization, instantiation, and analogy. We present a procedure model for Situational Reference Model Mining and demonstrate its usefulness by means of a case study. Existing techniques for Reference Model Mining are examined and mapped to their underlying design principles. This way, we are not only able to provide reference model designers with concrete guidelines regarding their choice of mining technique, but also point out research gaps for the development of new approaches to reference model mining.
Towards Situational Reference Model Mining - Main Idea, Procedure Model & Case Study
This contribution introduces the concept of Situational Reference Model Mining, i.e. the idea that automatically derived reference models, although based on the same input data, are intended for different use cases and thus have to meet different requirements. These requirements determine the reference model character and thus the technique that is best suited for mining it. Situational Reference Model Mining is based on well-known design principles for reference modeling, such as configuration, aggregation, specialization, instantiation, and analogy. We present a procedure model for Situational Reference Model Mining and demonstrate its usefulness by means of a case study. Existing techniques for Reference Model Mining are examined and mapped to their underlying design principles. This way, we are not only able to provide reference model designers with concrete guidelines regarding their choice of mining technique, but also point out research gaps for the development of new approaches to reference model mining.