Ph.D. Thesis - Business Informatics Group

Chapter 1 Introduction
In order to discuss communalities as well as differences between data exchange in the
data engineering field and model exchange in the model engineering field, an alignment of
the meta-modeling layers of both fields seems to be beneficial. Figure 2 shows this alignment
by using the 4-layer meta-modeling architecture proposed by the OMG [OMG05e].
On the layer M0 concrete objects reside which represent "real world" entities. Layer M1 determines
which objects shall be created for the domain of interest, described in a so-called
domain model. On layer M2, all concepts needed for describing domain models are defined,
so to say the language for describing domain models. In order to define the language specification
on M2 requires another meta-layer, i.e. layer M3, that covers meta-concepts necessary
for creating one’s own language, so to say it represents the meta-language. Normally,
as meta-language, a language is chosen which is able to describe itself, in order to ensure
that the M3 layer is self-contained.
M3
M2
M1
M0
Relational
DataModel
aRelational
Model
Data Engineering Model Engineering
No explicit formalism
XML
Schema
DataModel
anXMLSchema
Model
UML
aUML
Model
o1 o1 o1
MOF
SysML
aSysML
Model
o1
Legend
Correspondence
Transformation
Instance-Of
Figure 1.1: Meta-layers of Data Engineering and Model Engineering in Comparison
In the area of data engineering, integration scenarios concerning the layers M0 to M2 have
been considered, but no scenarios concerning the M3 layer have been investigated, because
in most cases no explicit meta-language has been applied to define the used data models 3 .
Furthermore, no user-defined data models are employed as is the case in model driven engineering
with user-defined modeling languages which gain more and more importance
through the trend to domain-specific languages (DSL) [Fow05]. In model engineering, the
integration scenarios are "lifted" one layer upwards, i.e., layer M1 to M3 are primarily concerned.
Nevertheless, similar problems occur when two modeling languages are integrated
on the M2 layer as when two schemas are integrated on the M1 layer. In particular, the
notion of heterogeneity as main driver for integration problems has been established in the
3 The main reason for this circumstance is that the relational data model and the XML schema data model represent
4
reflexive languages, i.e., they can be described in their own terms.