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a limited focus on conceptualizing the elements of the business model. In con-
trary, e3-value defines a conceptual model to describe the exchanges of value
among actors in a network. e3-value comes with a graphical syntax that is easy
understood by the domain expert. Furthermore, it allows the domain expert to
perform financial assessment of the value exchanges.
The Resource-Event-Agent (REA) ontology has its roots in the accounting
discipline and was originally developed as a reference framework to conceptualize
economic phenomena in an enterprise. In its proposal in 1982, McCarthy already
had the vision to facilitate the design of data structures of accounting information
systems by means of REA [4]. Since this time the REA model has been further
extended and evolved into a domain ontology [5]. All REA concepts are based on
well established concepts of the literature in economic theory - which is certainly
one of the strengths of REA. However, REA has no dedicated representation
format and, consequently, no graphical syntax. Thus, users may struggle when
describing the REA models leading to the impression that REA is a rather heavy-
weight approach. A dedicated graphical syntax - such as it exists for e3-value -
may help in overcoming this problem and may lead to a much more significant
adoption of REA. Accordingly, we have started the endeavor of developing a
domain specific modeling language for REA.
Most domain-specific languages (DSL) are small textual and usually declara-
tive languages. A DSL offers expressive power through appropriate notations and
abstractionsfocusedon-andusuallyrestrictedto-aparticularproblemdo-
main [6]. Besides textual DSLs, we see an increasing interest in domain-specific
modeling languages [7,8] based on dedicated meta-models and notations. van
Deursenet et al. claim [6] the following benefits of a DSL approach: They allow
solutions to be expressed at the level of abstraction of the problem domain. As
a matter of fact, domain experts themselves can understand, validate and of-
ten modify DSL programs/models. The DSL programs/models are concise and
self documenting to a large extent. They enhance productivity, reliability and
maintainability. DSLs allow for validation and optimization at the domain level.
When developing our REA-DSL we followed methodological steps that have
been suggested by Strembeck and Zdun for the systematic development of do-
main specific languages [9]. Amongst other variants, they describe the develop-
ment process for extracting a DSL from an existing system, which is appropriate
for our needs, because we extract the DSL from the existing REA ontology. Ac-
cordingly, we started with (1) the identification of elements in the REA ontology.
Next, we underwent a number of revision cycles of (2) deriving the abstract syn-
tax of the REA model including the core language model and the language
model constraints and (3) defining the DSL behavior, i.e. determining how the
language elements of the DSL interact to produce the intended behavior. Once
we had reached a stable state, we defined the DSL concrete syntax (4). Finally,
we implemented a modeling tool support for the DSL (5), but we skipped the
last step described in [9], i.e. integrating the DSL into a software platform, since
REA stays at the platform independent level.
