=Paper=
{{Paper
|id=None
|storemode=property
|title=iStarML: Principles and Implications
|pdfUrl=https://ceur-ws.org/Vol-766/paper02.pdf
|volume=Vol-766
|dblpUrl=https://dblp.org/rec/conf/istar/CaresF11
}}
==iStarML: Principles and Implications==
https://ceur-ws.org/Vol-766/paper02.pdf
CEUR Proceedings of the 5th International i* Workshop (iStar 2011)
iStarML: Principles and Implications†
Carlos Cares1,2, Xavier Franch2
1
Universidad de La Frontera, Av. Francisco Salazar 01145, 4811230, Temuco, Chile,
2
Universitat Politècnica de Catalunya, c/ Jordi Girona 1-3, 08034, Barcelona, Spain,
{ccares,franch}@essi.upc.edu
http://www.essi.upc.edu/~gessi/
Abstract. iStarML is an XML-based format for enabling i* interoperability. A
relevant difference with any other interoperability proposal is that iStarML is
founded under the assumption that there is not a common ontology guiding this
communication proposal. The different i* variants and even particular
applications proposing new language constructors forced to confront a
theoretical approach for supporting an interoperability approach in an evolving
and variable semantic scenario. In this paper we focused on the theories behind
the iStarML proposal, which include sociological, cybernetics and linguistics
approaches. Finally, we apply what these theories predict to the case of the i*
framework and its research community.
Keywords: i* Framework, iStar, variants, interoperability.
1 Introduction
The i* (iStar) framework has become a recognized and widespread framework in the
Information Systems Engineering community. Given that the i* framework
incorporates goal- and agent-oriented modelling and reasoning tools, it has been a
milestone for providing the basis, developing and spreading goal-orientation as a
relevant paradigm in Requirements Engineering and agent orientation in Software
Engineering. As a result of different interpretations and adoptions, several i* variants
have emerged, which have evolved at different maturity levels. Some of them have
reached the category of industrial standard (e.g., GRL in ITU-T) whilst others are in
some initial stages of development or were conceived for supporting a localized (in
scope and time) problem. Besides, there is a set of proposals that cannot be
considered i* variants because they simply include new or modified language
constructions. In [1] we have summarized a literature review reporting this fact.
As an effect of the past and even current proliferation of different i* variants, a
derived set of software tools and prototypes have been generated. However,
interoperability has been an elusive target. Although there is a clear core common to
virtually all i* variants, tool interoperability is founded on an agreement that implies
the existence of a shared ontology, which it has not been the case of i* variants.
†
This work has been partially supported by the Spanish project TIN2010-19130-C02-01.
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CEUR Proceedings of the 5th International i* Workshop (iStar 2011)
We have tackled the problem of proposing an interoperability framework for i*
variants. The aim is model interchange to “work together”, which is the deep meaning
of interoperability. We have called iStarML to the proposal of a XML-based format
language [2]. It incorporates structures which allows the representation of a wide set
of i* variants. As part of the theoretical approach that supports iStarML we have
presented the proposal from [3] as a key theory because it introduces the concept of
supermetamodel, which has been a key concept for demonstrating the reduction of
complexity of the translation among n i* variants. Besides, this framework introduce
degrees of semantic preservation which we have used to qualify the translation from
an i* variant to another [1]. The iStarML applications and usages that we have
promoted [4] illustrate the feasibility not only of interaction between different i*
variants but also the feasibility of using iStarML as a valid textual representation over
which other applications can be built.
2 Objectives of the Research
However, we have not explained the theoretical principles which have supported
the idea of enabling interoperability without having a shared and common ontology,
i.e. why and how interoperability can be sustained in a human poly-semantic scenario.
The goal of tackling this social perspective was to consider the Requirements
Engineering’s (and also Scientifics’) principle of proposing a better approach if there
a model (or theory) for understanding why.
In this paper we briefly present different theories that support the idea of having
communication without a shared ontology, some of them from linguistics, others from
cybernetics, and also from sociology of science. The social nature of these theories
gives us some information of what could be expected as research community and the
feasible social and technical scenarios that we could expect.
3 Scientific Contributions
Basic foundations in Computer Science affirm that interoperability requires a stable
semantic scenario to reach high levels of interoperability. However, this is not the
situation in the i* community because different tools have been inspired on different
i* variants. They do not only have different metamodels (syntax) but also they have a
different mapping to objects of reality (semantic) of their language constructs. We
present principles from Sociology of Science, Cybernetics and Linguistics which sup-
port the idea of enabling interoperability in spite of the absence of a shared ontology.
3.1 Sociology of Science Approaches
Sociology of Science embraces those studies that explain the foundations of science
(i.e., Philosophy of Science) from a sociological perspective. One of the relevant
contemporary philosophers has been Thomas Kuhn, who has modelled science
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CEUR Proceedings of the 5th International i* Workshop (iStar 2011)
evolution through discontinuous jumps [5]. Kuhn called these jumps “scientific
revolutions”, which are leaded by a reduced set of pioneers who change the basic
conceptualizations and build a new way of doing science. This new way of perceiving
and researching is called “scientific paradigm”. Each paradigm has an initial and
underlying ontology, which is “known” (in the beginning) only by the pioneers, who
try to communicate it and teach the new way of doing research using this ontology.
The impossibility of explaining the new ontology based on the previous ontology is
called by Kuhn “the incommensurability problem”. In spite of that, along time, the
ontology is spread, and used, not always as it was proposed but according to the
particular interpretations of the followers. This phase is called “the revolutionary
stage”. However, at some moment, the conceptualization converges to a stable and
shared ontology (the key concepts of the paradigms) and epistemology (what the
community accept as valid methods for knowledge production). When it happens, the
following phase, the normal-science stage, starts. The cycle continues when
theoretical anomalies appear (unsatisfactory explanations) and a new pre-
revolutionary stage germinates. Although the original Kuhn’s idea was to explain big
scientific movements, lately he recognizes that there are a lot of small and even
micro-revolutions which present the same behaviour. Figure 1 illustrates the stages.
Fig. 1. Kuhn’s model of a paradigmatic shift
Bourdieu’s theory of scientific fields [6] is the second approach from sociology of
science that we reviewed. In this theory the key concept is the symbolic capital.
Scientific behaviour is associated to fields that have, in its centre, the highest
concentration of symbolic capital; normally the leaders/pioneers of the fields occupy
these positions. They dominate the concepts and try to spread their ideas. Scientifics
try to maximize their symbolic capital by two ways: moving to the centre of the field,
which means to exactly follow the pioneers’ ideas and collaborate with them, or
generating new scientific fields by the intersection with other fields that allow them
occupying the centre of a new scientific field. Either in the zones of lower symbolic
capital or in the new fields, the concepts are not used as in the centre of the reference
scientific field. In Fig. 2, left, the idea of scientific field is illustrated.
In both theories it is recognized the fact that research activity without a fully shared
ontology, as it happens in the i* community, is feasible. Also, from these two
theories, we cannot expect the paradigms (i.e., the i* framework) be extended over
time or the i* field be kept the same way is in the centre and in the very far periphery.
A point of difference among these two approaches is the position about community
agreement on a shared ontology. From Kuhn it is predicted that having a shared
ontology stops the revolutionary stage and from Bourdieu it is predicted that we will
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CEUR Proceedings of the 5th International i* Workshop (iStar 2011)
always have uncontrolled interpretations and uses. However, this apparent contraction
is not real if we suppose that having static scientific fields is part of “normal science”.
3.2 Cybernetics Approaches
Cybernetics has been conceptualized as the General Theory of Control [7]. We can
rescue from Cybernetics both, classical and new conceptual frameworks. A classic
contributor has been Ross Ashby, who proposed a definition of intelligence from the
control perspective. Thus, intelligence is understood as a repertoire of behaviours;
therefore having more intelligence or variability means having a broader repertoire of
behaviours. In this theory it is said that humans are able to create intelligence
amplifiers in order to enlarge their control capabilities, which means to increase
variability. One of Ashby’s examples is the difference between the ships being loaded
quickly and easily by movements of a control handle, or slowly and laboriously by
hand [8]. Other intelligence amplifiers can be a dictionary, a sunglasses, a calculator
and of course, a modelling tool, because they improve the repertoire of behaviours.
In addition, contemporary cybernetics takes concepts as autopoiesis [9] to explain
that biological-based systems continuously regenerate the processes that produce
them (autopoiesis). This should be understood from both, as an internal point of view
(transformations) and as an external one (interactions). It is said that biological
systems are operationally closed systems which are self-produced and self-referred. It
means their actions are the effect of their interpretations (meaning-making process). It
also implies that operational distinctions (ontology) that use a system in order to guide
its interactions and transformations are not observable ones since they are internal to
the system. Therefore a biologically-based communication process emerges without
an explicit (non-external and non-shared) ontology. As an extension of that, and due
to intelligence amplifiers (e.g. modelling tools) are part of the interactions of the
system with its environment, then interoperability will take place if the meaning-
making process produces some interpretation (e.g. for an arriving model) which
improve variability.
3.3 Semiotics Approaches
Semiotics is about the interpretation of signs, syntax, semantics and pragmatics as
well. The main focuses are models that explain human communication from both
individual and collective perspectives. A relevant semiotic concept is language
expressions and their meanings, which changes depending on the community. What is
interesting for us are collective perspectives because they may model communication
in scientific communities. Semiotics considers that some language expressions can
reach stable meanings in the natural dynamic of meaning systems which implies that
these expressions can be used as intepretants, i.e. using in sentences that explain other
meanings. This is why an explanation might be completely understood by some
people meanwhile some others will have a different conception about it or partially
get what it means.
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CEUR Proceedings of the 5th International i* Workshop (iStar 2011)
Yuri Lotman [10] introduced the concept of semiosphere to explain commu-
nication inside medieval human cultures. Firstly he expresses that mono-semantic
systems do not exist in isolation. These related systems are part of a continuous
sphere of meaning called semiosphere. Lotman explains that the boundary is the area
of accelerated semiotic process (interpretations). This theoretical approach affirms
that in peripherical areas, where structures are “slippery”, less organized and more
flexible, the dynamic process meets with less opposition and, consequently, develops
more quickly. Then, one may say that the new semiosphere grows leaving in the
centre the dominant semiotic system constituted by a wide set of stable concepts. This
theory seems be very applicable for i* community as part of a more general software
engineering community and also for a particular i* variant community. From this
perspective the sentence from Lotman saying that the creation of meta-structural self-
descriptors (grammar) appears to be a factor which dramatically increases the rigidity
of the semiosphere’s structure and slows down its development, it can be easily
understood, e.g. by producing some social-based standard. In Fig. 2, right, the general
idea of semiosphere is illustrated.
Fig. 2. Concepts on Bourdieu’s Scientific Fields and Lotman’s Semiospheres
3.4 Implications for iStarML and the i* Research Community
After the theoretical analysis which only in part we have summarized here, some
conclusions emerge. Firstly, a complete shared ontology is neither a human requisite
for interaction nor for action, even when this communication is intermediated by
intelligence amplifiers as software tools. Therefore, an interoperability proposal
appears theoretically feasible. Moreover, we conclude that the structure of the
interoperability language should correspond to the way of a Bourdieu’s scientific field
or, similarly, to a Lotman’s semiosphere, i.e. core or stable concepts at the centre, and
the increasing of semantic variability and additional constructs towards the periphery.
If the inteoperability language may reproduce the semiosphere structure, then
intermediate structures should be in terms of core structures. Therefore, we proposed
iStarML using a concentric ring structure: (1) the core set of stable and common
abstract concepts (actor, intentional element, intentional link, dependency), (2) a core
set of common concepts established by a predefined set of main tag attributes (e.g.,
type=”softgoal”), (3) a space for specifying variations on existing but not so common
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CEUR Proceedings of the 5th International i* Workshop (iStar 2011)
attributes (e.g., value=”xor”) and (4) new elements (e.g. type=”norm” prior=”low”.
Therefore an iStarML message should be part of a meaning-making process, thus, it,
could be interpreted depending of the target i* variant community.
In addition, the application of these theoretical frameworks allows to derive some
conjectures about i* community: (1) If i* represents a materialization of a scientific
revolution then is not expected that the i* ontology keeps being an underlying
ontology. It will be explicitly expressed at some moment. (2) The externalization of
an i* ontology will not stop the scientific activity; it only will change its state.
Proliferation of interpretations will be stopped but “normal” (in the sense of Kuhn)
applications will be massively reported afterwards. (3) Following Lotman’s and
Bordieu’s theories, externalizing an ontology may be a very difficult job if central
scholars of the field are not involved. (4) Expressing an ontology will not avoid
intersections to other scientific fields, therefore, proliferation of applications with and
without i* modifications will take place.
4 Conclusions
The theoretical foundation for proposing iStarML, an interoperability proposal for i*
variants, has been reviewed. It included sociology of science, cybernetics and
semiotics. Following these theories about human communication and scientific
behaviour we have explained some reasons behind central features of iStarML.
However, the social nature of this theoretical framework allowed obtaining
conjectures (i.e. theory predictions) about the future of the i* community. Mainly they
point out to the expression and formalization of the i* ontology which stops the
revolutionary stage, fixes the grammar and establishes a new research period about
applications under a stable semantic scenario. In this hypothetical scenario iStarML
should be revised according to the inclusion of a set of language constructs from this
explicit formalization.
References
1. Cares, C., Franch, X.: A Metamodelling Approach for i* Model Translations. CAiSE 2011.
2. Cares, C., Franch, X., Perini, A., Susi, A.: Towards Interoperability of i* Models Using
iStarML. Computer Standards & Interfaces, 33(1) (2011).
3. Wachsmuth, G.: Metamodel Adaptation and Model Co-adaptation. ECOOP 2007.
4. Colomer, D., López, L., Cares, C., Franch, X.: Model Interchange and Tool Interoperability
in the i* Framework: A Proof of Concept. WER 2011.
5. Kuhn, T.: The Structure of Scientific Revolutions. The University of Chicago Press (1996).
6. Bourdieu, P.: The Specificity of the Scientific Field and the Social Conditions of the
Progress of Reason. Social Science Information 14(6), 1975.
7. Beer, S.: Cybernetics and Management. The English Universities Press (1967).
8. Ashby, W.R.: An Introduction to Cybernetics. Chapman & Hall (1957).
9. Maturana, H.R., Varela, F.J.: De Máquinas y Seres Vivos: Autopoiesis la Organización de
lo Vivo. Santiago de Chile, Editorial Universitaria (1998).
10. Lotman, J.: On the Semiosphere. Sign Systems Studies, 33(1) (2003).
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