Thiago Medeiros dos Santos, Rodrigo Bonacin
CESET, Unicamp and CenPRA, MCT, Rua Paschoal Marmo, 1888, Limeira, SP, Brazil
M. Cecilia C. Baranauskas
Institute of Computing, Unicamp, Caixa Postal 6176, 13083 970, Campinas, São Paulo, Brazil
Marcos Antônio Rodrigues
CenPRA, MCT, Rodovia Dom Pedro I, km 143,6, 13069-901, Campinas, São Paulo, Brazil
Keywords: Organizational Semiotics, Model Driven Architecture, Model Driven Engineering.
Abstract: Literature in Information Systems presents a set of approaches to analyzing and modeling the organizational
context in order to improve the quality of the computational systems. The research community also looks
for alternatives for aligning these approaches with Software Engineering techniques, which support the
large scale and low cost software production and maintenance. In this work is proposed an approach and a
tool to support the construction of computational models taken from the organizational models. This
approach is based on concepts, methods and techniques from MDA (Model Driven Architecture), and from
Organizational Semiotics, more specifically the MEASUR (Methods for Eliciting, Analyzing and
Specifying User’s Requirements). A MDA tool was constructed in order to realize the approach. The first
version of this tool provides means to model Ontology Charts. By using semi-automated transformations, it
is also possible to produce UML (Unified Modeling Language) class diagrams from the modeled Ontology
Charts. The tool features, design solutions, and capabilities are explained.
The design and use of computational systems are
susceptible to the organizational context where they
are immersed. Literature presents a set of
approaches to analyze and to model the
organizational context in order to improve the
quality of computational systems.
The research community also looks for
alternatives for aligning these approaches with
Software Engineering techniques, which support the
large scale and low cost software production, and
maintenance. Among the main difficulties is the
multidisciplinary nature of the problem, which
require methods, techniques and tools coming from
many domains, including: humanities, to understand
and model the organizational context; engineering,
to deal with aspects related to large scale and low
cost production; and technologies, to construct
appropriate techniques and tools.
In this work we propose an approach and tool to
support the construction of computational models
derived from the organizational models. The main
objectives of the proposed approach are to allow the
representation of the organizational context
semantics, and to provide a way to quickly produce
corresponding design models.
In order to achieve these objectives, we make
use of concepts, tools, and methods from Model
Driven Architecture (MDA) (OMG, 2003) and
Organizational Semiotics (OS) (Liu, 2000). OS
research explores the use of signs and their effects
on social practices. OS understands that each
organized behavior is affected by the
communication and interpretation of signs by
people, individually or in groups. This work is based
on Stamper’s school of OS (Stamper et al., 1988;
Stamper 2001), more specifically the use of the
MEASUR (Methods for Eliciting, Analyzing and
Specifying User’s Requirements) (Stamper et al.,
Medeiros dos Santos T., Bonacin R., Cecilia C. Baranauskas M. and Antônio Rodrigues M. (2008).
In Proceedings of the Tenth International Conference on Enterprise Information Systems - ISAS, pages 305-310
DOI: 10.5220/0001703703050310
1988) to model the semantic aspects of the
The MDA is a proposal that permits multiples
refinement of abstract models to generate the
systems code, through transformations (Gardner et
al., 2003). This work explores how Computation
Independent Models (CIM) can be refined using the
MDA approach.
A MDA tool was constructed in order to
materialize the approach. The first version of this
tool supports the modeling of Ontology Charts
produced during the Semantic Analysis Method
(from MEASUR). By using semi-automated
transformations, it is also possible to produce UML
(Unified Modeling Language) class diagrams from
the modeled Ontology Charts. In this paper, the tool
features are explained trough a small example of
ontology chart.
The paper is organised as follows: Section 2
presents the Model Driven Architecture and the
Semantic Analysis Method, Section 3 discusses the
proposed approach to produce Platform Independent
Models from Computation Independent Models,
Section 4 presents Sonar, the developed tool, Section
5 discusses the approach and further works, and
Session 6 concludes.
On this section we present concepts and methods
from Model Driven Architecture (MDA) and the
Semantic Analysis Method (SAM).
2.1 Model Driven Architecture
MDA is an Object Management Group (OMG)
proposal to promote an open solution for the
challenges related to constant business and
technological changes. To reach this objective in
MDA the application logic and the technological
issues of a specific platform are specified in models
of different abstraction levels.
In order to introduce MDA, firstly is presented
what the OMG means by the following concepts:
Architecture: The OMG adopts the Shaw and
Garlan (1996) concept. “The architecture of a
system is a specification of the parts and
connectors of the system and the rules for the
interactions of the parts using the connectors.”
(OMG, 2003, p.2-3) The MDA specifies kinds
of models and their relations.
Platform: “A platform is a set of subsystems and
technologies that provide a coherent set of
functionality through interfaces and specified
usage patterns, which any application supported
by that platform can use without concern for the
details of how the functionality provided by the
platform is implemented.” (OMG, 2003, p.2-3)
Viewpoint: “A viewpoint on a system is a
technique for abstraction using a selected set of
architectural concepts and structuring rules, in
order to focus on particular concerns within that
system.” (OMG, 2003, p.2-3)
Model: “A model of a system is a description or
specification of that system and its environment
for some certain purpose.” (OMG, 2003, p.2-2)
In the MDA specification three types of
viewpoints are proposed, as well as one model for
each viewpoint: the CIM (Computation Independent
Model), the PIM (Platform Independent Model) and
the PSM (Platform Specific Model). The CIM,
which is the focus of this work, has an important
role as a bridge between developers and domain
specialists. The CIM specifications are requirements
for PIM and PSM.
These models are specified according to
metamodels (models that describe models) that
should be specified according to metametamodels.
The metametamodels should be self-described.
Other metamodel layers could also be created if
necessary. According to MetaObjectFacility 2.0
(MOF) specification (OMG, 2006), the fundamental
concepts can be used to handle any number of
In MDA one model can be converted to another
model of the same system (usually more specific)
through a transformation process. The
transformation follows mappings, which can be
understood as a set of rules and methods to obtain a
new model from a previous one. The Model Type
Mappings allows specifying transformations from
any model built using types specified in PIM to
models expressed using PSM types. The Model
Instance Mappings allows specifying model
elements which should be transformed in a particular
According to Brown and Conallen (2005), some
times it is not possible to obtain automatic
transformations from model to model. The
transformation rules must be clear and unambiguous,
and should be able to programmatically access the
necessary elements of the models. Brown and
Conallen (2005) also emphasize that most of the
steps that involve natural language documents
reading are not typically suitable to MDA-style of
ICEIS 2008 - International Conference on Enterprise Information Systems
This is the main reason why automated
transformations from CIM to PIM are not common.
Usually, CIM models are based on textual
descriptions (i.e. Use Cases). However, better
structured CIM models, based on a visual language,
can help to construct systems aligned to business
and human factors, and even the “semi-automated”
transformations could bring benefits associated to
the cost, time and quality of the software. The next
section presents the Semantic Analysis Method as an
example of a CIM model constructed according to
Organizational Semiotics concepts.
2.2 Semantic Analysis Method
The Semantic Analysis Method (SAM) assists the
users or problem owners in eliciting and
representing their requirements in a formal and
precise model. With the analyst in the role of
facilitator, the required system functions are
specified in an ontology chart, which describes a
view of responsible agents in the focal business
domain and their behavior or action patterns named
affordances (Liu, 2000). Some basic concepts of
SAM adopted in this paper are based in Liu (2000):
“The world” is socially constructed by the
actions of agents, on the basis of what is offered
by the physical world itself;
“Affordance”, the concept introduced by Gibson
(1977), is used to express invariant repertories of
behavior of an organism made available by some
combined structure of the organism and its
environment. In SAM (Stamper, 1993) the
concept introduced by Gibson was extended by
Stamper to include invariants of behavior in the
social world;
“Agent” can be defined as something that has
responsible behavior. An agent can be an
individual person, a cultural group, a language
community, a society, etc. (an employee, a
department, an organization, etc.);
“An ontological dependency” is formed when an
affordance is possible only if certain other
affordances are available. The affordance “A” is
ontological dependent on the affordance “B”
means that “A” is only possible when “B” is also
“Determiners” are properties which are
invariants of quality and quantity that
differentiate one instance from another;
“Specialization”, agents and affordances can be
placed in generic-specific structures according to
whether or not they possess shared or different
The concepts of Semantic Analysis are
represented by means of ontology charts, which
have a graphical notation to represent agents
(circles), affordances (rectangles), ontological
dependencies (lines drawn from left to right), role-
names (parentheses) and whole-part relations (dot).
Ontology Chart can be understood as a CIM model
given that it focuses on organization and
requirements. However, the SAM addresses issues
that are not represented in any of the UML diagrams
and it provides a different way of thinking about the
organization if compared with the Object Oriented
paradigm. Consequently the transformation from
Ontology Chart to Class diagrams is not a trivial
task. It is also possible to see the Ontology Chart as
a kind of CIM metamodel (not adopted in this
work), which specifies the semantics of other
The rationale to construct the transformation
rules is based on a previous work that deals with
how to build UML Class Diagram informed by
SAM (Bonacin et al., 2004). Nevertheless,
additional aspects must be considered in CIM to
PIM transformations. The following steps are
proposed to build CIM to PIM transformations: (1)
create the transformation rules, (2) develop the
metamodels for CIM, (3) analyze which rules need
human intervention, (4) create the heuristic
metamodels, (5) design the interfaces to facilitate the
human intervention, and (6) develop the
Regarding the rule creation, in this work was
adopted a group of ten heuristic rules proposed in
Bonacin et al. (2004). The next step was the
development of meta-models for ontology charts.
The KM3 (Kernel MetaMetaModel) language
(Atlas, 2005) facilitated the description of
Metamodels in MOF (MetaObject Facility) (OMG,
2006), and the Ecore (Budinsky et al.; 2003).
Figure 1 presents an UML diagram for the
Ontology Chart Metamodel. The concept of
“element” was created to describe anything at the
diagram. Affordance is a central concept at the
diagram. Role-name and agents are special types of
affordances. Affordances may also include
determiners and specializations. Ontological
dependencies link affordances.
Figure 1: Ontology Chart Metamodel.
Whole-part is a special type of ontological
dependency and an ontological dependency may
also include a role-name.
After constructing the Metamodel, the proposal
was to find out the heuristics that could be directly
automated, and which rules need human
intervention. An example of a non-directly
automated transformation is the creation of classes
or operations from affordances names. It is
necessary a human intervention to say whether an
automated rule should be applied or not, and to
decide which automated rule should be applied: to
transform the affordance into a class or operation.
If the second option is selected, additional
information is necessary to construct the PIM.
Figure 2 shows an intermediary model proposed to
describe this information. It has the “HAffordance”
Class with three attributes: Operation indicates if the
affordance will be mapped to an operation or to a
class, ClassId indicates the class that will contain the
operation, and affordanceId identify the affordance
that will be mapped.
The next step is the design of the interfaces for
end-user intervention. A wizard based solution was
adopted in this work. The last step is the
implementation of the transformations. They map
data from the ontology chart metamodel and the
heuristic model to PIM (UML models).
As Figure 3 shows, the Ontology Chart modeling
tool, named Sonar, has the basic features of a CASE
(Computer-Aided Software Engineering) tool,
including: icons to model the diagram elements,
copy, paste, undo, redo, zoom, and export as image.
The fragment of the ontology chart diagram in
Figure 3 will be used to explain how the
transformation occurs internally in this modeling
tool. This fragment has the “society” as the root
agent; “person” and “thing” is ontologically
dependent of “society”; and “owns” is ontologically
dependent of “person” and “thing”.
Figure 2: Example of Heuristic Metamodel.
Figure 3: Sonar Main Window.
After modeling the Ontology Chart, the user can
transform it to UML models by using wizards on the
“Tool” menu. Figure 4 shows an example of wizard
where designers can specify which affordance will
be mapped to operation, and associate them to
classes (affordances mapped to classes) that will
contain it. For example the class “Person” contains
the method “owns”. By associating “owns” to
“person” a heuristic model is created following the
heuristic metamodel specification. The heuristic
ICEIS 2008 - International Conference on Enterprise Information Systems
model contains the necessary data to determine the
appropriated transformations that will be applied.
Figure 4: Example of wizard to human intervention.
Figure 5 shows an overview of the
transformations implemented by the Sonar tool. At
the CIM level there are two models: the ontology
model constructed according to the diagram, and the
heuristic model that is a result of human intervention
through wizards. These models follow the
metamodels specified in MOF and/or Ecore.
Internally the models are represented according to
the XMI format (OMG, 2007).
Transformations (Figure 5) were constructed
using the ATL (Atlas Transformation Language)
(Atlas, 2006). “ATL provides developers with a way
to produce a number of target models from a set of
source models.” (Atlas, 2006, p.1).
Figure 5: Sonar Transformations.
There are two source models (ontology and heu-
ristic) that produce target models. After producing
the PIM a number of transformations, can be applied
to produce PSM models, such as: to C++, to EJB,
and to SQL. According to Figure 5, in this version of
Sonar we can transform the UML to a Java model
and finally to Java code.
Figure 6 is a graphical representation of a
possible UML model produced from the ontology
model presented at Figure 3. This model contains
three classes produced from the “Person”, “Thing”
and “Society”. The user has decided to transform the
“Owns” affordance in a method of the class
“Person”. The method could return, for example, the
thing(s) that the “Person” owns. Alternative models
can be produced according to the human
intervention, such as, one model without the
“Society” class.
Figure 6: Constructed UML Model.
The first version of Sonar can be understood as a
starting point to further research. One important
feature of the proposed approach is the possibility of
following the process: the capacity to detect the
origin and follow the tracking from the source model
to the produced model. Although the process
includes human intervention, the decisions are
registered on the heuristic models. Thus, it is
possible to verify how elements of the PIMs were
constructed from the CIM elements.
However, Ontology Charts do not produce a
complete PIM; consequently the PSM is also
incomplete. In a real life situation, the produced PIM
should be complemented with many details before
the transformation to PSM. In addition, important
decisions need human intervention (i.e. if implicit
elements of the CIM, like “society” should or not be
explicit in the implemented system). Nevertheless, it
is necessary to consider two main aspects:
The produced model can be a valuable starting
point for the design of a complete and consistent
PIM. It produces a set of domain classes that are
closely related to the real context. Usually design
models closely related to real contexts result on
systems more reusable and easier to maintain;
The approach can also be applied to equally well
define CIM (in addition to Ontology Chart), to
produce a more complete PIM, e.g.: a “norm
based model”, from the OS norms analysis
method (Stamper et al., 1988), could be used in
order to model the dynamic aspects of the
organization, consequently improving the
produced PIM.
It is also important to consider the possibility to
produce other diagrams from the Ontology Charts.
Ontology has been used to deal with problems of
systems integration. The Semantic Web (W3C,
2007) makes use of ontology to process the content
of information. The Ontology Charts could be used
to produce models based on technologies such as:
OWL (Web Ontology Language) (W3C, 2004). As
Semantic refers to meaning, and meaning are
socially created by humans, is expect to create a
more faithfulness Ontology if we start from a
Computer Independent Model.
The design and use of computational systems are
susceptible to the organizational context where they
are immersed. In this paper is proposed an approach
to produce computational models transformed from
the organizational ones. This approach has its basis
on techniques and methods from MDA and SO.
An Ontology Chart modeling tool, named Sonar,
implements the main proposed ideas. It shows the
possibility of generating PIM from CIM, using semi-
automated transformations. Among the main
benefits are the visibility of the transformation
process, and the production of an initial design
model closely related to the real context concepts.
We thank colleagues from CESET and IC at
Unicamp, and CenPRA for valuable contributions.
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