## 2 Related Work  
To manage the methodological gap between ontology and modeling schema, the DOGMA model [8] introduces a double articulation ontology model. The ontology has two main components: ontology base and ontology commitments. The ontology base contains the standard concept level model elements such as taxonomy and concept assertions. The second component is used to describe the domain-specific ontology rules. These rules can be used to determine the available properties and domain specific integrity constraints. Considering the practical guidelines for ontology development, a design pattern-oriented method was proposed in [9]. The proposed modular design approach includes the following six main design patterns, covering the different key aspects of the ontology:  
* Structural pattern,
* Syntactic pattern,
* Content pattern,
* Presentation pattern,
* Consideration pattern. Considering the area of Software Engineering (SE) in general, there is a rich literature on the application of ontology tools in SE processes. One of the first proposals on ontology support [10] focused on the software quality issues. The main reason for the importance of ontology tools in SE is that experience shows lack of domain knowledge [11] to be a very risky situation in the software development process. The excellent survey of [PERSON] and [PERSON] [12] presents all the important achievements of this research field. Their survey shows that the whole area of software development and software technology is involved in the development of ontology-based model extensions. In the majority of proposals, a separate domain ontology model is constructed covering the specific SE development phases. The constructed and validated ontology models are  
Figure 1: Architecture of the evaluation framework. mapped manually or partially automatically into SE models. With regard to automatic mapping, the work of [PERSON] [13] presents a method for code generation directly through a high-level and detailed ontology specification, resulting in good consistency of the generated code. A similar approach is presented in [14]; an ontology-oriented programming method is proposed in which the specification of a problem solution is expressed in the form of an ontology. Regarding the semi-automated integration approaches, the constructed ontology model can be used to generate standard SE design models. For example, in [15], the UML document was extended with annotations generated from the related ontology. There have been proposals in the literature focusing on special schema-oriented extensions of the base ontology model. In [16], the conflicts caused by multiple inheritance were investigated in detail, with a a semi-automatic approach proposed to deal with such conflicts. The work of [17] highlighted the importance of integrating OOP concepts with standard knowledge engineering approaches. Based on these considerations, we focus here on the integration of ontological and schematic approaches. The goal of our work is to investigate the feasibility of a property-based ontology approach. An important related modeling approach is the field of Formal Concept Analysis (FCA). FCA [18; 19] provides tools to manage and investigate concept sets generated from an input formal context. A formal context is defined as a triplet \((G,T,I)\), where \(I\) is a binary relation between \(G\) (a set of objects) and \(T\) (a set of attributes); \((x,y)\in I\) is met if and only if the attribute \(y\in T\) is true for the object \(x\in G\). Two derivation operators \((g,f)\) are introduced as mappings between the powersets of \(G\) and \(T\). For \(A\subseteq G,B\subseteq T\),  
\[f:2^{G}\to 2^{T}f(A)=\{m\in T|\forall o\in A:(o,m)\in I\}\]  
\[g:2^{T}\to 2^{G}:g(B)=\{o\in G|\forall m\in B:(o,m)\in I\}\]  
For a context \((G,T,I)\), a formal concept is defined as a pair \((A,B)\) for which the following conditions are met:  
* \(A\subseteq G\)
* \(B\subseteq T\)
* \(A=g(B)\)
* \(B=f(A)\).