Domain-Specific Modeling Languages (DSMLs) have received great attention in recent years and are expected to play a big role in the future of software engineering as processes become more view-centric. However, they are a “two-edged sword”. While they provide strong support for communication within communities, allowing experts to express themselves using concepts tailored to their exact needs, they are a poor vehicle for communication across communities because of their lack of common, transcending concepts. In contrast, General-Purpose Modeling Languages (GPMLs) have the opposite problem - they are poor at the former but good at the latter. The value of models in software engineering would therefore be significantly boosted if the advantages of DSMLs and GPMLs could be combined and models could be viewed in a domain-specific or general-purpose way depending on the needs of the user. In this paper we present an approach for achieving such a synergy based on the orthogonal classification architecture. In this architecture model elements have two classifiers: a linguistic one representing their “general-purpose” and an ontological one representing their “domain-specific” type. By associating visualization symbols with both classifiers it is possible to support two concrete syntaxes at the same time and allow the domain-specific and general-purpose notation to support each other - that is, to form a symbiotic relationship.

Although domain-specific modeling tools have come a long way since the modern era of model-driven development started in the early 1990s and now offer an impressive range of features, there is still significant room for enhancing the flexibility they offer to end users and for combining the advantages of domain-specific and general-purpose languages. To do this, however, it is necessary to enhance the way in which the current generation of tools view metamodeling and support the representation of the multiple, ?ontological? classification levels that often exist in subject domains. State-of-the-art tools essentially allow users to describe the abstract and concrete syntaxes of a language in the form of metamodels and to make statements in that language in the form of models. These statements typically convey information in terms of types and instances in the domain (e.g., the classes and objects of UML), but not in terms of types of types (i.e., domain metaclasses), and types of types of types, and so on, across multiple classification levels. In essence, therefore, while they provide rich support for ?linguistic? metamodeling, the current generation of tools provides little if any built-in support for modeling ?ontological? classification across more than one type/instance level in the subject domain. In this paper, we describe a prototype implementation of a new kind of modeling infrastructure that, by providing built-in support for multiple ontological as well as linguistic classification levels, offers various advantages over existing language engineering approaches and tools. These include the ability to view a single model from the perspective of both a general-purpose and a domain-specific modeling language, the ability to define constraints across multiple ontological classification levels, and the ability to tie the rendering of model elements to ontological as well as linguistic types over multiple classification levels. After first outlining the key conceptual ingredients of this new infrastructure and presenting the main elements of our current realization, we show these benefits through two small examples.