Formalization of the classification pattern: survey of classification modeling in information systems engineering

Area of Science:

• Information Systems Engineering (ISE)
• Formal Methods
• Domain Modeling
• Ontology

Background:

• Formalization is increasingly adopted in information systems development.
• Classification systems are central to domain modeling, posing challenges due to formal complexity and ontological issues.
• The powerset concept offers a formal benchmark for classification pattern expressiveness.

Purpose of the Study:

• To analyze the formalization of the classification pattern within Information Systems Engineering (ISE).
• To survey the historical evolution of formalization approaches in ISE literature.
• To assess current ISE formalization methods against the powerset benchmark for expressiveness.

Main Methods:

• Literature survey tracing theoretical mathematical works to ISE applications.
• Analysis of various formalization proposals for classification patterns.
• Benchmarking against the Linnaean taxonomy formalized using powersets for expressiveness.

Main Results:

• The ISE community is in the early stages of formalizing classification patterns, particularly concerning expressiveness.
• Existing formalization efforts often lack the expressiveness demonstrated by the powerset benchmark.
• Varying adoption rates are linked to historical factors and the need for semantic explanations within different ISE communities.

Conclusions:

• Formalizing the classification pattern in ISE requires greater expressiveness, exemplified by powersets.
• There is a significant opportunity to accelerate adoption by clarifying the expressiveness of formal structures.
• Improving the formalization of classification patterns can lead to substantial advancements in domain modeling.