Power-Modelling

Toward a More Versatile Approach to Creating and Using Conceptual Models

Ulrich Frank

University of Duisburg-Essen, Essen, Germany

ulrich.frank@uni-due.de

Keywords:

DSML, Interactive Modelling, Multi-level Modelling, Empowerment.

Abstract:

The prospects of conceptual modelling are widely undisputed. Nevertheless the current practice of conceptual

modelling remains unsatisfactory. Usually, modelling languages offer primitive concepts only—with respec-

tive effects on productivity and model quality. The creation of models is restricted to early phases of system

life-cycle. Hence, the beneﬁts of models in later phases are ignored. Furthermore, the creation and use of

conceptual models is still restricted to experts only. In this paper, the outline of a new modelling paradigm,

referred to as power-modelling, is presented. It builds on the potential of domain-speciﬁc modelling languages

(DSML), application frameworks and reference models. It regards models as the primary medium to perceive,

interact with and change systems and the environment they are supposed to operate in during the entire sys-

tem life-cycle. For this purpose, power-modelling is built on an extensible set of multi-level DSML that ﬁt

the conceptual perspectives of a wide range of prospective users and a common representation of models and

code, which allows overcoming the notorious problem of synchronizing models and code.

1 INTRODUCTION

If maturity comes with age, a few decades of research

and application should have resulted in a widely per-

fected state of conceptual modelling. There are in-

deed various signs of maturity. Both in Information

Systems and Computer Science it seems undisputed

that conceptual models are a prerequisite to manage

the complexity of large software systems. Further-

more, it is acknowledged that conceptual models are

much better suited than code to involve prospective

users and other stakeholders in the process of devel-

oping software. The beneﬁts of conceptual models for

designing software systems do not come as a surprise.

After all, software systems are linguistic artefacts. On

the one hand, they are realized with some kind of im-

plementation language. On the other hand, as non-

physical artefacts they can be perceived—and used—

by humans only through some kind of linguistic rep-

resentation. At best, this linguistic representation cor-

responds to the language used in the targeted do-

main. Conceptual models are aimed at reconstructing

domain-speciﬁc languages in a way that prospective

users perceive them as familiar, while at the same time

they allow for transformations into implementation-

level languages. By structuring and eventually au-

tomating the transformation of models into code, as

it is pursued by approaches to model-driven software

development (Atkinson and K

uhne, 2003; France and

Rumpe, 2007), conceptual modelling is promising to

substantially improve the productivity of developing

software systems.

But conceptual modelling is not restricted to mod-

elling software systems. Exploiting the potential of

information systems often requires re-organizing re-

spective action systems. Consequently, correspond-

ing modelling approaches, such as business process

modelling, turned out to be a good choice for sup-

porting people with analysing and (re-) structuring ac-

tion systems. The insight that corporate action sys-

tems do not only comprise business processes, but

also other subjects, such as goals, resources or or-

ganizational structure, contributed to the emergence

of approaches to enterprise modelling (Scheer, 1992;

Ferstl and Sinz, 2006; Frank, 2013). By integrat-

ing conceptual models of software systems with con-

ceptual models of action systems, enterprise models

promise to provide a foundation for jointly analysing

and designing information systems and the relevant

organizational context. Since more and more orga-

nizations have given up developing software on their

own, the original idea of using conceptual models

for designing software systems does not ﬁt the de-

mands of many organizations anymore. At the same

Frank U.

Power-Modelling Toward a More Versatile Approach to Creating and Using Conceptual Models.

DOI: 10.5220/0005423800090019

In Proceedings of the Fourth International Symposium on Business Modeling and Software Design (BMSD 2014), pages 9-19

ISBN: 978-989-758-032-1

time, the ever growing complexity of IT infrastruc-

tures created additional challenges. Again, concep-

tual models of IT infrastructures, including various

representations of their high-level structure or archi-

tecture, have evolved as a remedy. While respective

models are often part of enterprise modelling meth-

ods, they are also featured by approaches to enterprise

architecture, which in general aim mainly at managers

and therefore emphasize a higher level of abstraction

(Lankhorst, 2005; Proper et al., 2010; Buckl et al.,

2010). Therefore, conceptual modelling supports a

wide range of activities related to analysing, design-

ing and managing IT infrastructures and correspond-

ing action systems. A relatively large research com-

munity, both in Information Systems and Computer

Science, may serve as further evidence for the matu-

rity of the ﬁeld.

However, our brief assessment of the ﬁeld’s con-

tributions may be deceptive—and maturity may have

its downsides, too. As we shall see, there are seri-

ous reasons for not being satisﬁed with the state of

the art in conceptual modelling. There are even rea-

sons to challenge the current paradigm of concep-

tual modelling. In any case, it does not seem ap-

propriate to further follow existing paths of research

by focussing solely on problems within this paradigm

without leaning back once in a while to reﬂect upon

other ways to conceptualize, develop, maintain and

use models. While I had my doubts for some time

whether we are doing the right thing, I started to in-

tentionally abandon some characteristics of concep-

tual modelling which I had not only taken for granted,

but which I used to preach enthusiastically. I am

still in the—sometimes painful, sometimes exciting—

process of realigning my perspective and my research

agenda. However, a few ideas have emerged that I

regard as promising. One of them is subject of this

paper. I dared calling it “power-modelling”, not only

to express that it might be suited to substantially pro-

mote the power of modelling as a tool to create and

modify systems, but also to empower users by sup-

porting them with sophisticated, but convenient in-

struments to use and modify the systems they work

with.

The paper starts with a critical review of the cur-

rent state of the art. Subsequently, an overview of

approaches that address certain shortcomings of con-

ceptual modelling is given. Against this background,

I will describe the idea of power-modelling by out-

lining the foundational concepts and by illustrating

how it could be implemented. Since the respective

research is in a very early stage and faces serious chal-

lenges, the conclusions will especially focus on future

research.

2 CONCEPTUAL MODELLING: A

CRITICAL REVIEW

There are various reasons, why the current state of

conceptual modelling might not be regarded as satis-

factory (Frank, 2014a). At ﬁrst, there is the sobering

fact that the dissemination of conceptual modelling

in practice is still rather modest. Many software de-

velopers still regard it as dispensable. Managers per-

ceive it as a cost-driver that does not deliver measur-

able beneﬁt. Finally, prospective users are often not

keen to look into conceptual models, nor are they ca-

pable of designing them on their own. The unsatis-

factory adoption in practice may be contributed to a

lack of respective professional education among to-

day’s workforce. However, I am afraid, we would

take the easy way out, if we were satisﬁed with this

explanation. There are other, more essential reasons

for questioning the power of current approaches to

conceptual modelling, which also may, in part, hin-

der its acceptance and dissemination in practice. They

relate to the economics of modelling and the psycho-

logical assumptions underlying the construction and

perception of conceptual models.

2.1 Economics of Modelling

With respect to economics of modelling, three as-

pects are of particular relevance. At ﬁrst, there is

the productivity of creating, analysing and modify-

ing conceptual models, i.e. the time these activities

take for a certain outcome. While modelling produc-

tivity depends on modellers’ skills and experiences, it

is also affected by the available modelling languages

and tools. A modelling language can contribute to

productivity by providing reusable artefacts and by

allowing for abstractions that foster reuse and adapta-

tion of models. Currently, most modelling languages

are restricted to a few semantic primitives that remind

of basic ontologies like the one suggested by (Bunge,

1977) or (Grossmann, 1983). While generic concepts

such as “entity type”, “class”, “attribute”, etc. can

be applied to any domain—which is the purpose of

a general ontology—they require modellers to recon-

struct all concepts of a model from scratch. Hence,

they promote a wide range of reuse, which should im-

prove economies of scale e.g. of modelling tools, but

in a particular case, their contribution to productivity

is very poor. Imagine, you would have to describe a

domain such as accounting and you were restricted to

a language that consisted of generic concepts like the

ones provided by the ERM and the UML! Further-

more, modelling languages provide only a few ab-

straction concepts such as classiﬁcation, generaliza-

Fourth International Symposium on Business Modeling and Software Design

tion or encapsulation. As a consequence, similarities

between a range of models can often not be accounted

for by abstracting on a set of common properties. The

lack of abstraction is especially painful in business

process modelling, where reuse is widely restricted

to copy&paste (Frank, 2012). Second, there is little

protection of investment. The use of conceptual mod-

els is widely restricted to the build time phase. In

later phases, models are used for documentation only,

if they are used at all. Even in those cases, where

models were used to generate code, they will usually

get devalued over time, because during maintenance

changes are directly applied to code and synchroniz-

ing models and code, beside representing a serious

challenge, does not happen. Third, the beneﬁt of mod-

els depends on their quality. However, judging the

quality of conceptual models is a demanding task and

requires experts. Current modelling languages and

tools hardly contribute to model quality, since their

generic concepts allow for almost any kind of absurd

models as long as they are syntactically correct. From

a managerial perspective there is the additional prob-

lem that the economics of modelling is hard to judge.

While it is often not trivial to determine modelling

costs in advance, quantifying the beneﬁts of models

ex ante is almost impossible. As long as managers

are not convinced that modelling is suited to generate

substantial beneﬁt, the lack of legitimate quantiﬁca-

tion methods creates a serious obstacle to conceptual

modelling in practice.

2.2 Cognitive Capabilities

Conceptual modelling is based on basic assumptions

that most members of the modelling community—

including myself—are convinced of. First, there is

the assumption that the analysis and design of com-

plex systems recommends a rational approach, i.e.

an approach that is characterized by the differenti-

ated consideration of pros and cons and that puts em-

phasis on justifying decisions. Second, related to the

ﬁrst assumption, following a Kantian tradition, a ra-

tional perspective demands for focussing on concepts.

Conceptual modelling is typically aimed at the recon-

struction of terms used in the domain of interest. Re-

ferring to existing terminology is supposed to make

conceptual models accessible by people working in

the domain. At the same time, a reconstruction is

required in order to create concepts that ﬁt the spe-

ciﬁc modelling purpose and that facilitate mapping

to implementation languages. As a consequence, it

it common to specify concepts according to the def-

initions of types or classes in implementation lan-

guages. While these basic ideas make perfect sense,

they are based on an idealization that is seriously chal-

lenged by research in cognitive psychology. There is

a plethora of work that shows the rather limited abil-

ity of most humans to precise and consistent think-

ing, for an overview see (Kahneman et al., 1982).

Furthermore, the way people acquire and use con-

cepts is often in clear contrast with the deﬁnitions we

use in conceptual modelling (Lakoff, 1990). Among

the most relevant insights are the following: Con-

cepts are often not associated with (extensional) deﬁ-

nitions, but rather with a few typical examples (proto-

types”). Conceptual categories are often perceived as

having no clear boundaries (membership gradience”,

(Lakoff, 1990), p. 12). The last example is of es-

pecial relevance for our investigation: Most cognitive

models are embodied with respect to use.” ((Lakoff,

1990), p. 12) As a consequence, we cannot expect

prospective users to be much interested in and capable

of thinking in concepts as we use them for modelling

purposes.

2.3 Preliminary Conclusion

Our brief analysis of the current state of conceptual

modelling resulted in a number of problems. That

does not mean, however, to question the idea of con-

ceptual modelling in general. In order to cope with

complexity and change there is no alternative for us

other than to somehow develop models. Without ab-

straction not only our understanding of systems and

of the world in general will remain poor, but so would

be our ability to design and implement systems. Nev-

ertheless, those problems should make us think. In

particular, there are three areas that demand for more

attention. There is need to promote modelling pro-

ductivity. For this purpose, reuse has to be fostered

by providing modelling constructs that incorporate

domain-speciﬁc semantics. To promote model qual-

ity, the reusable artefacts offered to users should be

thoroughly developed and tested. At the same time,

economies of scale are crucial. For this purpose, an

artefact needs to be reused in a wide range of cases,

which may create a conﬂict to modelling productiv-

ity. To improve the involvement of prospective users,

models, new forms of presenting concepts and mod-

els to users are required. Since there is evidence that

people imagine or learn concepts by associating them

with contexts of use, it might be advisable to develop

modelling environments that focus on the use of con-

cepts. The use of models during later phases of the

system life-cycle demands for developing scenarios

that illustrate the respective beneﬁt. In addition, tech-

nical challenges, such as solving the notorious prob-

lem of synchronizing code and model have to be ad-

Power-Modelling - Toward a More Versatile Approach to Creating and Using Conceptual Models

dressed.

3 SELECTED APPROACHES

There have been various approaches that address

some of the problems elucidated above. Some of them

are aimed at improving modelling productivity and

model quality, while others focus on implementation

issues or on user involvement.

3.1 Focus on Productivity and Quality

Reference models are based on a convincing idea. By

developing models that serve as a reference for cer-

tain domains, the costs for realizing large models in

respective domains could be reduced substantially. At

the same time, reference models should be developed

with outstanding care and expertise. Therefore, they

should effectively improve model quality. Further-

more, reference models do not only stress a descrip-

tive intention, i.e. representing a domain as it is, but

also a prescriptive intention, i.e. representing concep-

tualisations that seem especially favourable for the fu-

ture development of organizations in the targeted do-

main. Despite their convincing foundation, the dis-

semination of reference models in practice remained

extremely modest. Domain-speciﬁc modelling lan-

guages (DSMLs) are build on a similar idea. Different

from general-purpose modelling languages (GPMLs),

they comprise domain-speciﬁc concepts, thus free-

ing modellers from the need to specify these con-

cepts from scratch. At the same time, DSMLs fea-

ture usually, but not necessarily, a concrete syntax

that is adapted to representations known in the do-

main they cover. In addition to promoting productiv-

ity through improved reuse and ergonomics, DSML

also contribute to model quality, since their syntax

and semantics facilitate preventing models that are all

too strange. Modelling is more convenient, and the

range of possible models is clearly restricted com-

pared to a GPML.

While DSMLs are certainly suited to address the

productivity challenge, they are not the silver bullet of

conceptual modelling, since they face a fundamental

conﬂict of system design. On the one hand, increasing

productivity demands for concepts that are speciﬁc to

a particular domain, i.e. that incorporate a high de-

gree of domain-speciﬁc semantics. On the other hand,

economies of scale demand for DSMLs that cover a

wider domain, i.e. that include a smaller degree of

domain-speciﬁc semantics. This fundamental conﬂict

of designing DSMLs is illustrated in ﬁg. 1

Level of (domain-specific) Semantics

Potential Productivity Gain

Scale of Reuse

Figure 1: The fundamental conﬂict of designing DSMLs.

3.2 Focus on Implementation

If one regards a model mainly as an instrument for de-

veloping software, the transformation of models into

code is a major aspect of increasing the value of mod-

els. Some time ago, Wiederhold et al. proposed an ap-

proach, called “megaprogramming” to substantially

promote the productivity of programming large ap-

plication systems (Wiederhold et al., 1992). Even

though they do not explicitly speak of modelling,

there are clear relations to conceptual modelling in

their work. They suggest to compose large software

systems from “megamodules”. Megamodules can be

thought of as domain-speciﬁc abstraction: megamod-

ules “capture the functionality of services provided

by large organizations like banks, airline reservation

systems, and city transportation systems. ... The

concepts, terminology, and interpretation paradigm of

a megamodule is called its ontology.” (Wiederhold

et al., 1992), p. 89. However, the representation of

megamodules as well as their composition happens on

the code level only. Therefore, they are hardly suited

for being used by non-experts. It is, however, con-

ceivable to combine the idea of megamodules with a

representation that corresponds more clearly to a ter-

minology users are familiar with. Even though meg-

amodules, like DSML, promote domain-speciﬁc arte-

facts, their use is based on a bottom-up approach in

the sense that a system is created from some kind

of building block without providing a blueprint for

the overall design. Application frameworks stress a

top-down approach. An application framework rep-

resents an architecture and the partial implementa-

tion of a class of application systems. “Black box”

frameworks can be adapted only through interfaces,

while “white box” frameworks allow for modifying

their code. Frameworks can substantially boost the

productivity of application development. However,

while the adaptability of black box frameworks is

Fourth International Symposium on Business Modeling and Software Design

limited, using white box frameworks efﬁciently re-

quires considerable effort. Similar to megamodules

the representation of frameworks is usually restricted

to code. Approaches to model-driven software de-

velopment take advantage of conceptual models for

designing systems. At the same time, they promote

implementation productivity by aiming at generating

software systems from models (France and Rumpe,

2007), (Stahl and V

olter, 2006). To cope with a mul-

titude of platforms and programming languages, spe-

ciﬁc effort has been put on generating platform- and

language-independent representations that allow for

a straightforward transformation into particular im-

plementations (Mellor, 2004), (Pastor and Molina,

2007). Even though model-driven software develop-

ment is suited to improve development productivity

and software quality, it remains unsatisfactory with

respect to the evolution of software systems: Usually

it is not possible to generate an entire software system

from models, i.e. there is need for manual extensions.

As a consequence, the evolution of code and models

has to be synchronized. While there are a few ap-

proaches that address the challenge of synchronizing

models and code (e.g. (Balz et al., 2010), (Agrawal,

2003)), they are not satisfactory, because they cannot

always ensure consistency.

3.3 Focus on User Involvement

To some extent, the development of DSML and corre-

sponding editors is aimed at making modelling more

convenient for users who are not trained in concep-

tual modelling. The idea of using models at run time

(Blair et al., 2009), while also contributing to the

protection of investments, may be suited to motivate

more people to use models: as a conceptual represen-

tation of the systems they interact with and may want

to modify. However, recent research in this area is

mainly focused on software engineering aspects such

as synchronisation of models and systems, e.g. (Song

et al., 2011), or self-adapting systems, e.g. (Amoui

et al., 2012), (Morin et al., 2009). Krogstie proposes

using models during the entire life-cycle of a system

to emphasize user empowerment (Krogstie, 2007).

For this purpose, modelling should not longer be re-

stricted to system development. Instead, for mod-

elling to have a “larger effect”, he proposes “to en-

able all knowledge workers to be active modelers.”

(p. 305). Enterprise software systems should be pre-

sented to their users as “interactive models”, the use

of which is “about discovering, externalizing, captur-

ing, expressing, representing, sharing and managing

enterprise knowledge.” (p. 306). In addition to known

approaches to enterprise modelling, Krogstie stresses

the need for more intuitive representations of models,

such as “visual scenes for pro-action learning” and

descriptions of the relevant context that focus on ac-

tions (p. 308). Using models as objects and objectiva-

tion of organizational knowledge work and of individ-

ual learning is appealing. However, Krogstie remains

vague about the realization of his vision. He suggests

a “model-generated workplace (MGWP)” that “is a

working environment for the business users involved

in running the business operations” (p. 312), but he

does not provide details of how to accomplish “inte-

grated modelling and execution platforms” (p. 308).

4 OUTLINE OF

POWER-MODELLING

The idea presented in this section was inspired by var-

ious streams of work, some of which are described

above. It is also a result of our long-standing-work

on enterprise modelling that confronted us with some

serious problem we were not able to solve as long

as we were still bound to the traditional principles of

conceptual modelling and of implementing modelling

tools. Hence, the outline of power-modelling is also

an attempt to suggest a new paradigm of creating and

using conceptual models.

4.1 Objectives and Challenges

Against the background of our previous discussion,

the following objectives mark desirable features of a

future conception and realization of modelling.

Objective O1: A powerful approach to conceptual

modelling should enable the use of models during the

entire life-cycle of a system. Rationale: The com-

plexity of enterprise systems demand for a represen-

tation that users are able to understand, not only to ob-

tain a better comprehension of a software system, but

also of the the context, since an increasing part of an

enterprise is represented by its software systems. At

the same time, people need (cognitive) models any-

way to make sense of software systems and of organi-

zations. Therefore, explicit models that ﬁt the cogni-

tive capabilities of users should be suited to increase

organizational transparency. Objective O2: Concep-

tual models that represent software systems and the

context they operate in should be interactive. Ratio-

nale: In order to serve as a universal interface to en-

terprise systems that fosters user empowerment, mod-

els need to allow for navigation, for searching and for

modifying their states—not only during build time,

but during run time. Objective O3: Conceptual mod-

els should provide access to their conceptual foun-

Power-Modelling - Toward a More Versatile Approach to Creating and Using Conceptual Models

dation, i.e. to the modelling language they are de-

ﬁned with, i.e. respective modelling tools should be

self-reﬂective. Rationale: Users may want to get a

better understanding of the concepts the models they

interact with are based on. Furthermore, advanced

users may even want to change those concepts. Ob-

jective O4: Conceptual models should be constructed

from concepts that are used in professional discourse

in the relevant domain. Rationale: Domain-speciﬁc

concepts promote modelling productivity and make

the use of modelling concepts more intuitive. Objec-

tive O5: Conceptual models of an enterprise should

cover multiple perspectives and foster their integra-

tion. Rationale: The complexity of many organiza-

tions goes along with specialization which in turn re-

sults in different professional perspectives and lan-

guages. In order to satisfy the demand for provid-

ing users with representations they are familiar with,

models of an enterprise need to account for different

perspectives. On the one hand, that relates to pro-

viding modelling concepts which correspond to the

technical language that is characteristic for a certain

perspective. On the other hand, it should also be

possible to present a model using different notations,

both graphical and textual, in order to satisfy differ-

ent cognitive styles. Objective O6: To increase the

economics of modelling economies of scale have to

be increased by promoting reuse. Rationale: Today,

the effort it takes to develop elaborate models is of-

ten still prohibitively high. The above objectives cre-

ate considerable challenges. Among those, three are

hard to overcome within the current paradigm. Aim-

ing at both, modelling concepts that reﬂect particu-

lar, domain-speciﬁc technical languages, and that pro-

mote economies of scale faces an obvious conﬂict:

A language can either be more domain-oriented or

built for serving more general purpose. Using mod-

els at run time that allow interacting with and eventu-

ally changing a software system demands a tight in-

tegration of models and code in order to keep their

changes in synch. However, this is almost impossi-

ble due to limitations of prevalent programming lan-

guages. The elements of a model on M

are repre-

sented as objects on M

, even though they are con-

ceptually located on M

. This is the case, too, for

the representation of metaclasses in meta model edi-

tors. As a consequence, there is need to generate code

(objects on M

cannot be further instantiated), which

creates the notorious problem of synchronizing mod-

els and code. The lack of abstraction concepts in pro-

cess modelling languages creates a serious obstacle

for reuse. While generalisation/specialisation may be

regarded as a suitable approach, it cannot be applied

to processes in a straightforward way: To satisfy the

substitutability constraint (Liskov and Wing, 1994),

specialisation has to be monotonic, which is impossi-

ble to achieve for process models (Frank, 2012)

4.2 Cornerstones of Power-Modelling

For the vision of power-modelling to become real, the

current paradigm is not sufﬁcient. There is need to

change our perspective on conceptual modelling and

to aim at a different linguistic foundation—both of

modelling and implementation languages. The fol-

lowing aspects mark cornerstones of a conception of

power-modelling.

Emphasis on DSML: DSMLs that are recon-

structed from existing technical terminologies (objec-

tive O4) promise clear advantages with respect to pro-

ductivity, model quality and comprehensibility. For

this purpose, we can build on an existing integrated

set of DSMLs for enterprise modelling (Frank, 2013).

Multi-Level Modelling: In order to overcome the

fundamental conﬂict of designing DSMLs (objectives

O4 and O6), a multi-level language architecture is

proposes. It is inspired by the deﬁnition and reﬁne-

ment of technical languages in practice. On a more

generic, textbook” level, concepts are introduced that

are supposed to ﬁt a wide range of more speciﬁc do-

mains. For that purpose, they remain intentionally

abstract and underspeciﬁed. On more speciﬁc lev-

els that could cover, for example, particular indus-

tries, concepts are reﬁned and added. This process

of stepwise reﬁnement may in the end lead to nu-

merous language levels, from more generic, over re-

gional” to local” DSMLs. Multi-level modelling de-

scribes a language architecture that allows for an ar-

bitrary number of classiﬁcation levels. This allows

to achieve both, a wide range of reuse, i.e. beneﬁ-

cial economies of scale, on higher levels, and a high

productivity that is enabled by more speciﬁc DSML

that reuse concepts of more generic DSML. Since all

DSMLs are integrated in one language architectures,

users can navigate all classiﬁcation levels they are in-

terested in (objective O3). Fig. 2 illustrates a multi-

level language architecture and corresponding editors.

For a detailed description of multi-level modelling see

(Frank, 2014b).

Common representation of models and code: Us-

ing models during the entire life-cycle of a systems

create the challenge of synchronizing models and

code, which is caused by the fact that current imple-

mentation languages allow for one or two classiﬁca-

tion levels only. There are, however, a few languages,

which are based on the recursive golden braid” archi-

tecture that facilitate systems with more classiﬁcation

levels. Among these languages, XMF (Clark et al.,

Fourth International Symposium on Business Modeling and Software Design

Reference DSML

Language Designer

Organisational Unit

Position

Specific DSML

(Local „Dialect“)

Organisation Analyst

Department

Team Market Analyst

Particular Organisation

Model

Manager

Marketing Department

Quality Circle

Product Group PG 1

Market

Analyst MA2

Market Research

Team

Committee

Quality Circle

Meta Modeling Language

Meta Language Designer

MetaEntity

Association

MetaAttribute

Metamodel Editor

Organisation Schema Editor

Specific Organisation Editor

specifies

foundation of X

creates X

Figure 2: Illustration of multi-level language architecture.

2008b), (Clark et al., 2008a) is particularly suited for

supporting power-modelling. First, it enables an ar-

bitrary number of classiﬁcation levels. Second, it

is accompanied by a (meta) modelling environment,

Xmodeler, that features a common representation of

models and code, hence, it eliminates the need for

synchronizing models and code and facilitates the use

of models during the entire life-cycle of a system.

In order to develop a suitable foundation of multi-

level modelling and multi-level enterprise systems,

we modiﬁed the metamodel of XMF (Frank, 2014b).

By overcoming the separation of model and code,

every system can be seen as a collection of models

which can be used interactively (objective O2) with

multiple representations that can be exchanged based

on an implementation of the model-view-controller

pattern (for details see (Clark et al., 2008a)).

Wider conception of conceptual modelling: In the

existing paradigm, a conceptual model is created from

the concepts of a modelling language, typically ar-

ranged in diagrams that represent some kind of a

graph. However, modelling can also be thought of

as an act of conﬁguration that makes use of existing,

more generic models and of DSML. In that case, mod-

elling is more interactive, where a respective mod-

elling system suggests alternative modelling options

and requests user preferences. Since many users make

sense out of action context rather than of singular con-

cepts, interactive modelling should also go along with

the representation of the context a model is supposed

to address. A prototypical context could be provided

by an enterprise model that integrates various per-

spectives on the enterprise (Frank, 2013) (objective

O5). Furthermore, such a wider conception would in-

clude to not restrict modelling to drawing diagrams.

Instead, models would be accessible through the ele-

ments of a graphical user interface, through tables or

even through plain text. While it makes sense to re-

Power-Modelling - Toward a More Versatile Approach to Creating and Using Conceptual Models

Figure 3: Deﬁnition of a DSML for modelling organizational structures of universities.

strict models to types or classes, a wider conception

of modelling would also include models that comprise

objects on M

using similar (graphical) representa-

tions to enable their interactive use. For example:

The representation of a business process type could

be supplemented by similar representations of busi-

ness process instances (for an example in the context

of so called “self-referential enterprise systems” see

(Frank and Strecker, 2009), p. 14).

Ubiquitous use of (multi-perspective) models:

Models are proposed as the primary medium to per-

ceive, interact with and change systems—and the en-

vironment they are supposed to operate in during the

entire system life-cycle. To serve this purpose, mod-

els have to be prepared for various perspectives to sat-

isfy different skills and needs. Then they would no

longer be a tool for system analysts and designers,

but for everybody acting responsibly in an environ-

ment that is penetrated by information systems. As

a consequence, power-modelling would contribute to

empowering users by giving them (guided) access to

a system’s conceptual foundation and by supporting

communication with other stakeholders.

4.3 Illustration

The following scenarios highlight selected aspects of

power-modelling.

Reﬁnement of DSML: Developing a DSML for

modeling organizational structures may appear as a

fairly trivial undertaking. However, this is not the

case. First, a remarkable concept variance has to be

accounted for. For example: A term like “depart-

ment” may represent clearly different kinds if orga-

nizational units in different environments. In a uni-

versity, a department consists of institutes and chairs.

In some industrial enterprises, a department is part of

a head department, in others not. Applying the idea

of multi-level modelling to this domain would sug-

gest developing a reference DSML for organization

modelling. Such a reference DSML would include

a descriptive graphical notation. A respective edi-

tor could be used by organization analysts to create

an organizational schema for a certain domain, e.g.

a particular organization or a range of organizations

of a certain kind. Finally, this more speciﬁc DMSL

would be used by local managers to build a particular

organizational structure that corresponds to the previ-

ously deﬁned schema. Fig. 3 illustrates the deﬁnition

of a DSML for modelling organizational structures of

universities by using a more general DSML that rep-

resents a textbook-level terminology.

The resulting DSML could then be used for cre-

ating an editor that facilitates modelling the organiza-

tional structure of a particular university. The result-

ing model is located on M

. Even though it does not

satisfy the abstraction usually demanded for by con-

ceptual modelling, it is still beneﬁcial to use a graphi-

cal notation that corresponds to that of the DSML de-

ﬁned on M

. Such a model would enable interactive

access to particular organizational units—and also al-

low for navigating to the speciﬁcations of respective

concepts on higher classiﬁcation levels.

Modelling as Interactive Conﬁguration: Instead

Fourth International Symposium on Business Modeling and Software Design

CO 1

CO 2

CO 3

CR 1

CR 2

CR 3

S 1

S 2

Figure 4: Conﬁguration through stepwise selection of intended model properties.

of creating a model bottom-up from the concepts pro-

vided by a modelling language, the following sce-

nario shows how a model can be created by combin-

ing reference models, application frameworks, multi-

level modelling and a common representation of mod-

els and code to not only create models more conve-

niently but to realize a corresponding implementation

at the same time. The scenario is based on the exis-

tence of a repository of various reference models that

were created with a set of integrated DSMLs. It is

aimed a modelling and thereby implementing an or-

der management system for food retailing. Fig. 4 il-

lustrates the use of a tool that facilitates the conﬁg-

uration of particular models from an existing set of

reference models. At ﬁrst, the user would specify the

targeted domain by selecting options from lists pre-

sented by the modelling tool. Based on that selection,

a set of possibly ﬁtting business process types would

be presented to the user. After selecting one business

process type, the user could reﬁne the process model

by selecting from properties that are offered by the

system. In case, the control ﬂow requires further mod-

iﬁcation, the user could modify it using a respective

DSML for business process modelling.

5 CONCLUSIONS AND FUTURE

RESEARCH

The presented outline of a new approach to creating

and using conceptual models has a twofold motiva-

tion. On the one hand, it stresses the need for lean-

ing back once in a while and questioning assumptions

that we tend to take for granted. On the other hand,

it presents the cornerstones of a more versatile and

powerful approach to conceptual modelling. The pre-

sentation of the vision is focussed on illustrating the

idea in order to inspire a discussion about its beneﬁts

and about potential enhancements. Nevertheless, the

required foundation, especially a multi-level language

architecture and a common representation of models

and code, is available. It has been developed during

the recent years (Frank, 2014b), (Frank and Strecker,

2009) and builds on a mature meta-programming lan-

guage (Clark et al., 2008b). While it required to give

up certain assumptions that we had taken for granted,

such as the rigid dichotomy of instantiation and spe-

cialization, it opens new ways of designing and imple-

menting systems that are represented to users as mod-

els on different levels of abstraction. This paradigm

shift requires not only giving up “standard” language

architectures like MOF (Object Management Group,

2006), but also replacing existing implementation lan-

guages. Therefore, it may be regarded by some as not

realistic. However, if we, at least in academia, do not

Power-Modelling - Toward a More Versatile Approach to Creating and Using Conceptual Models

give up the widespread ﬁxation on mainstream tech-

nology, progress will hardly be possible. There is still

a long way to go. Future research needs to address

the development of reference models on different lev-

els of abstraction that are speciﬁed with respective

DSML. There is also need to develop advanced pat-

terns of interaction that support the conﬁguration and

modiﬁcation of models. Last but not least, it is re-

quired to overcome the limitations of current imple-

mentation languages by moving to more ﬂexible lan-

guages architecture like the one XMF is based on.

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