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A reference model is an abstract framework for understanding significant relationships among the entities of some environment. It consists of a minimal set of unifying concepts, axioms and relationships within a particular problem domain [ Bibliography#ref88].

A reference model is not a reference architecture. A reference architecture is an architectural design pattern indicating an abstract solution that implements the concepts and relationships identified in the reference model [ Bibliography#ref88]. Different from a reference architecture, a reference model is independent from specific standards, technologies, implementations or other concrete details. A reference model can drive the development of a reference architecture or more than one of them [ Bibliography#ref99].  

It could be argued that a reference model is, at its core, an ontology. Conventional reference models, e.g., OSI [ Bibliography#ref1010], RM-ODP [ Bibliography#ref44], OAIS[ Bibliography#ref1111], are built upon modelling disciplines. Many recent works, such as the DL.org Digital Library Reference Model [ Bibliography#ref99], are more ontology-like.

Both models and ontologies are technologies for information representation, but have been developed separately in different domains [1 Bibliography#ref13 13]. Modelling approaches have risen to prominence in the software engineering domain over the last ten to fifteen years [1 Bibliography#ref12]. Traditionally, software engineers have taken very pragmatic approaches to data representation, encoding only the information needed to solve the problem in hand, usually in the form of language, data structures, or database tables. Modelling approaches are meant to increase the productivity by maximising compatibility between systems (by reuse of standardised models), simplifying the process of design (by models of recurring design patterns in the application domain), and promoting communication between individuals and teams working on the system (by a standardisation of the terminology and the best practices used in the application domain) [1 Bibliography#ref13]. On the other hand, ontologies have been developed by the Artificial Intelligence community since the 1980s. An ontology is a structuring framework for organising information. It renders shared vocabulary and taxonomies which models a domain with the definition of objects and concepts and their properties and relations. These ideas have been heavily drawn upon in the notion of the Semantic Web [1 Bibliography#ref13].

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