Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
Construction of a Complex Adaptive Systems Pattern as an Epistemological
Lens for E-Government Systems
Adrian Krolczyk∗ , Christian Senf∗ and Nils Cordes∗
∗
Systems Analysis and IT
Technical University Berlin, Germany
Email: [Adrian.Krolczyk, Christian.Senf, Nils.Cordes]@sysedv.TU-Berlin.de
Abstract
So far, no coherent approach exists to identify,
describe and analyse socio-technical systems. In this
paper we propose such a concept, by drawing on three
theories: complex adaptive systems, enterprise architecture and pattern theory. We endeavor to combine
elements of these theories and resolve the incoherence among them. We have also tested the empirical
relevance of this approach for the case of semantic
standardization in Germany. Thereby we show, that the
approach is sufficiently feasible, correct and useful.
1. Introduction
There is still no common understanding of ’interoperability’ [1] [2]. A widely shared meaning of
the term ’inter-operate’ is that systems are able to
operate together as if they where one [3]. In the broad
sense, interoperability is understood as the ability of
socio-technical systems to work together. From a more
technical viewpoint it is the ability of information and
communication technology systems to meaningfully
and seamlessly exchange information and use the information that has been exchanged [3] [4].
From a socio-technical point-of-view we have to
deal with the interoperability of complex systems. We
suggest that in order to understand interoperability
we have to understand the complex interdependencies
between and within complex systems. A promising
approach is complex adaptive systems theory. It is concerned with the basic principles and emergent patterns
of complex systems.
Although we see a multidisciplinary recitation of
complex adaptive systems theory, there exists no coherent instrument for the identification, description and
analysis of real-world socio-technical systems in the
sense of complex adaptive systems until now. In order
to resolve this deficit we propose the construction of a
complex adaptive systems pattern as an epistemological lens for systems in the context of e-government.
With this approach we combine previously incoherent
coupled streams of research.
We apply this pattern to the semantic standardization
system of Germany, a core service for nearly all egovernment systems.
Our approach consists of the following steps: we
use the theoretical building blocks of complex adaptive
systems, enterprise architecture and pattern theory to
construct our epistemological lens (section 2) for the
interpretation of the empirical data (section 5).
From the point-of-view of the developed theoretical framework it doesn’t matter what kind of sociotechnical system is observed - that is the strength of
the approach. The derived patterns will grasp specifics
of e-government systems through their context description, the identified complexity-sources or the chosen
solution space, but are not limited to them, as there
have to be relations to non-e-government systems, as
well.
However, empirically we have proved only one case
in the context of e-government, and therefore the validity of the argument given above has to be proved by
a non-governmental case. Through our approach, the
dichotomy between e-government systems and non-egovernment systems can be dissolved, without losing
the characteristics of each research area.
2. Theoretical background
We start from the general assumption, that within the
sciences the interpretation of real-world phenomena
proceeds through usage of symbols. In the sense of
Cassirer [5], symbols can be defined as interpreted
signs shaped by the underlying ’modes of thought’ [6]
(originaly: symbolic forms), connected with meaning,
through which relations and structures in the world can
be found.
978-0-7695-3869-3/10 $26.00 © 2010 IEEE
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Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
These ’modes of thought’ guide the interpretation of
what we see - how the perceived data is represented
within us. Through different ’modes of thought’ we
interpret what we see differently. We endow the empirical data with different meanings; and finally, according
to Berger and Luckmann [7] we construct different
realities through different symbols.
In this sense, an epistemological lens can be understood as a symbolic prism (incorporating special
’modes of thought’), through which the applying individual can grasp new relations and structures in the
’world’.
We conceive the following three theories as different
’modes of thought’; each theory contains core-symbols
with inter-subjective shared meanings, guiding the
epistemological process. For the identification of the
core-symbols we investigated nearly 100 scientific
publications in the context of complex adaptive systems and enterprise architecture.
We work under the assumption, that each theory
(’mode of thought’) contains a set of core-symbols.
Each core-symbol can be understood as an ’epistemological axis’ that propagate a semantic field - filled
with other symbols ’floating’ in it. For example, in the
context of enterprise architecture we have identified 50
relevant terms, ’floating’ in-between the six suggested
’epistemological axes’. These axes are not given an
arbitrary meaning by an individual, but are developed
through a socio-cultural evolution within the scientific
community.
The set of core-symbols and their relations constitute our coherent terminological and theoretical basis.
Our selection of theories has been motivated by the
following reasons:
• Our aim was to capture the real-world phenomena we investigated in our case study through a
coherent theoretical structure, which is open for
further development.
• The inherent knowledge of enterprise architecture
theory reflects very well the particular, concrete
and local criteria of socio-technical systems. It
can therefore be described as a ’thick’ theory (in
the sense of [8]).
• The theory of complex adaptive systems by contrast is ’thin’; more abstract and informed by
universal principles, which makes it applicable
to a wide range of phenomenon areas with the
drawback of being not very ’practical’.
• Pattern theory provides a very useful approach
through a sharable common vocabulary which
grasps knowledge in a direct and reusable way.
The derivation of the core-symbols within each
theory is presented in a compressed form.
2.1. Complex adaptive systems (CAS)
CAS promises to be a way to understand phenomena
in our physical and living environment and to design
new solution paths for ’global challenges’. It stands
for a paradigm shift in the Kuhnian sense, from
complicated but controllable, to complex and selforganisational systems; for a change from top-down to
bottom-up thinking. This shift leads to changes in our
world view ’as if the professional community had been
suddenly transported to another planet where familiar
objects are seen in a different light’ [9].
Pioneered in 1968 by Buckley [10], CAS reached
a broader audience through the works of Holland
[11] [12], Gell-Mann [13] and Kauffman [14] [15]
in the 1990s. In the last decade we could perceive a
multidisciplinary recitation of CAS [16]–[22] - often
with different labels like iasos, icas, thinking systems,
ace ... A thorough analysis of actual developments is
presented by Pathak et al. [23].
As a starting point we use a general definition based
on Holland [11] and Fromm [24] of CAS as ’a complex, self-similar collectivity of interacting adaptive
agents’. The term complexity refers to two different
aspects: first we have to deal with networks made up of
many interwoven agents acting in parallel. Secondly,
although we might be able to define local rules for
the actions of the agents, due to non-linearities, the
collective behavior cannot be predicted by statistical
techniques. Adaptation addresses the mechanisms of
learning and changing through experiences.
Due to the different contexts of application, we are
today confronted with a variety of terms describing
or defining CAS. Some works (e.g. [25]) use the
seven basic elements aggregation, non-linearity, flows,
diversity, tagging, internal models and building blocks
defined by Holland [11]. Anderson [26] distinguishes
four properties interacting entities, self-organization,
co-evolution and recursion. Rhodes [18] proposes the
five core elements agents, schemata, fitness function(s),
connections and state of the system, whereas Janssen
[20] enumerates the ten characteristics emergence, coevolution, sub optimal, requisite variety, connectivity,
simple rules, iteration, self-organizing, edge of chaos
and nested systems.
Based on our epistemological interest to identify, describe and analyze real-world socio-technical systems,
we identified the following four core-symbols of CAS:
Agents of the system - The term agent has to be
used in a context-sensitive way as the agents are different in each system [24] and can range from subatomic
particles to planets [27]. In socio-technical systems it
is used broadly for individuals, teams [28] or whole
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Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
organizations like enterprises [25] or governments [20]
[19] which all show adaptive behavior.
According to Rhodes [18] the basic unit of organization can be grasped through the concept of an initiative,
defined as the cooperative ’interlocked behaviors’ of
individuals through the organizing modes markets,
hierarchies and networks. This conception results in
individuals and organizing initiatives as the two basic
agent types.
Rule sets - Rules play a central role in the conception of CAS. The key idea is that the complex, collective behaviors of agents are based on simple (universal)
rules [11], [12] in the sense of a kaleidoscope [20].
According to this model, the behavior of the system
depends on the collection of rules [26] as they organize
the system [16]. For Zhou [19] rules serve as strategies
that define responses to different internal and external
stimuli.
In socio-technical systems we will find different rule
sets for different individual agents and types of agents
and also the possibility of rule set exchanges [21].
Emergent patterns - In CAS the term emergence
refers to phenomena that result from basal relations
of the agents. These basal relations are described
as ’coupled, context-dependent interactions’ [12] or
properties on a local, respectively micro level, which
unfold global patterns of behavior at a higher level of
abstraction [18] [19] [21] [26].
Due to the large number, parallel existence and
high dynamic of these basal relations the emergent
patterns can also be considered as non-linear functions
of the system [23]. In this sense, the properties of
the emergent patterns are distinct from those of the
basal agents and cannot be predicted by the latter.
Each emergent pattern describes, for an extended time
scale, a specific dynamic of the system. In order to
understand these dynamics we need emergent patterns
at different levels of granularity and abstraction [21].
Of particular importance are the feedback mechanisms from the emergent patterns to the agents. They
inform the behavior of the agents, changing in the case
of humans, their thinking, and hence the behavior of
the system itself [24] [20]. For example, the formation
of new initiatives as a process of ’enactment’ by
individual agents results in new emergent patterns
which affect in turn the whole system [18].
In the context of socio-technical systems, we have to
consider that the access of the agents to the emergent
patterns is always an interpretive one, even more so
since the emergent patterns are not always visible. As a
consequence, there will be some sort of mapping layer
that channels the interpretations of the agents and thus
the interpretation-based acts will vary among different
agents. According to Rhodes [18], the interpretation,
enactment of initiatives and feedback of emergent patterns are generators of non-linearity in organizational
systems.
For the sake of completeness, the phenomena emergence and self-organization are deeply interwoven.
Order creation through self-organization in the physical
world is described by Kauffman [14], [15]. In short,
self-organization can be defined as a process in which
emergent patterns appear without external engagement
on the system [26]. Summarized we can say that
based on self-organization, the occurrence of emergent
patterns is a result of the basal relations of the agents
that changes the systems behavior through feedback
loops.
Symbolic interactions - The interactions of the
agents are an essential part of CAS. In socio-technical
systems the acts of humans are based on symbolic
interpretation. According to Cassirer, humans have
the anthropological status of an ’animal symbolicum’
as we live in a symbol world supplementary to the
physical universe. Therefore, he distinguishes between
signals as ’operators’ which are part of the physical
world of being and symbols as ’designators’ which are
part of the human world of meaning - symbols have
a functional value, respectively, meaning is a function
of symbols [5]. According to Goodman [29], plural
symbol systems constitute plural realities.
Transfered to CAS, we propose symbol theory as
a promising approach to understand the impacts of
symbolic interactions on the occurrence of emergent
patterns as different symbol systems result in different interpretations and thus in different acts of the
agents. A first attempt at the analysis of forms/signals,
meanings/symbols (as conceptualizations of reality)
and form-meaning pairs can be found by Steels [30].
2.2. Enterprise architecture (EA)
In this section we develop a basic understanding
of the term ’enterprise architecture’ as there exists no
general accepted definition [31] [32] [20]. Methodologically we identify six central aspects (core-symbols) in
the context of enterprise architecture research. Based
on this sample, we span a terminological frame in order
to unfold a coherent term and meaning of enterprise
architecture. The six aspects are systems, complexity,
technology, methodology, language and time.
Systems aspect - ’Every system has an architecture’
- this statement marks the origin of architecture considerations. The term system refers, for example, to information systems, system architecture or system theory.
The possibility of a hierarchical decomposition of
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Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
systems in subsystems is mentioned by many authors
as it is the basis of all object- respectively serviceoriented approaches as well as for the discussion of
software reuse (e.g. [33]).
We can describe the conception of systems according to Fromm [24] as reductionistic in terms of
separating a system in parts and to focus on their
interactions. According to Harmon [34], an enterprise
is not one giant system but a conceptual system of systems containing interactive physical entities. Through
the nested characteristics of real-world systems we can
establish a relationship between EA and CAS.
Complexity aspect - Complexity is the object of
investigation of a whole scientific community although
it is hard to find a universal definition. In a general
sense complexity appears in systems with a great
number of elements, with a high degree of interdependencies among them and a non-linear respectively nondeterministic quality. The term complexity addresses
in the context of EA ,a multiplicity of phenomena
like complex systems, organizations, environments, architectures, software, processes, decisions, technology,
networks, models or structures - to name a few.
Technology aspect - Technology is an essential part
of every socio-technical system. It has an enabling
function as it provides new forms of organization [35]
[36] [37]. A great interest exists in the alignment of
business and IT spheres. An organization has to be
able to develop a technology landscape that keeps
up with the continuously changing (strategic) business
requirements [38]. In literature, technology represents
the bottom layer/level on which all other layers build
on [39] [32].
Dreyfus and Bala [40] point to the inherent ambivalence in socio-technological systems. Technological artifacts open new information sources for the
organization, but can also filter out unexpected but
essential information - ’the components of information
systems are imbued with symbolic meaning that shapes
and is shaped by the using organization’.
Methodology aspect - Methodologies govern the
’unfolding’ of organizations. Every EA approach is
linked with at least one methodology. Methodologies
provide an argumentative basis for the selection of
views and guide the participating parties in all process steps with the appropriate level of granularity.
Methodologies and frameworks are deeply interwoven
and mark, seen from an idealized point-of-view, the
polar ends of a continuum [20], [31], [37], [38], [41].
Due to a paradigm shift from complicated to complex
systems new methodologies will appear and will in
part overcome the former [20] [38].
Language aspect - In the context of EA a multi-
complexity
system
time
methodology
language
technology
Figure 1. Aspects of Enterprise Architectures
plicity of modeling languages with different aims and
methodologies coexists. This heterogeneity reflects the
necessity to grasp the manifold views and levels of an
EA in an appropriate way. Every domain ’speaks’ its
own language, develops its own models and uses its
own means for the visualization [31], [36], [39], [41].
As a consequence of the heterogeneity of languages
it is very difficult to establish adequate links between
the models. Communication gaps and inconsistencies
result from an absence of integrative mechanisms.
A promising approach consists in providing a basis
of common shared concepts to which all other modeling languages could be ’docked’. A principle way is
sketched by Jonkers et al. [39].
Time aspect - The time dependencies of EA manifest primarily through the time-to-market-driven environments, the change over time of stakeholders requirements and the evolution of the organization into
the future [40] [33]. A general concept to handle time
complexity is the modeling of ’life cycles’ [42] [41].
Of particular interest is the ability of organizations
to prevent its digital informations from falling into
oblivion through time.
EA-hexagon - The presented six aspects correlate
to each other in manifold ways and are separated
only for analytical reasons. As a basic structure of
these interdependencies we can use analogous to the
Civilisational Hexagon of Senghaas [43] the metaphor
of the hexagon for the context of enterprise architecture
(see Fig. 1).
Based on the EA hexagon we define the term enterprise architecture as a discourse containing enterprises
as multilayer systems (system-of-systems) in contexts of
high complexity and temporal flow as well as for analyzing and designing these systems with the means of
modeling languages, technologies and methodological
patterns.
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Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
2.3. Pattern theory
The term pattern is widely used in the scientific community. In general we can distinguish between conceptional and non-conceptional patterns.
Non-conceptional patterns are ’observations of any
kind showing nonrandom structure and therefore containing information on the mechanisms from which
they emerge’ [22]. In the following section we will
discuss in a short review the three conceptional pattern
approaches of Alexander [44], Gamma et al. [45] and
Buschmann et al. [33] as they developed the basic
principles of pattern definition, language, classification
and description.
The textual form of the two works of Alexander
[44] [46] differs from standard academic publications.
But there are similarities to the dialog-form of Plato or
the aphorisms of Wittgenstein in the way that content
and form of the works exist in a strong interdependent
relation. An aim for Alexander is the intermediation
of a holistic point-of-view about function and design
of architecture. For this, he designs a pattern concept
which is the groundwork for an universal patternlanguage.
A common definition of a pattern is: ’Each pattern
is a three-part rule, which expresses a relation between
a certain context, a problem, and a solution’ [44].
Patterns provide a means for the communication and
verification of gained experiences. They represent a
kind of ’vehicle’ for structuring, documentation and
communication of problem-solution pairs in changing
contexts. The Alexandrian pattern language consists of
253 patterns and offers the possibility to ’create’ global
phenomena (e.g. infrastructure of a city) through the
implementation of lower patterns (e.g. build your own
house) in a bottom-up approach. The language provides this through a continuos connection of patterns
of different levels of abstraction. Through the contextualization, the pattern is bound into a hierarchical
and/or heterarchical structure. A predetermined path of
using patterns doesn’t exist. The possible combinations
of patterns among each other are manifold, although
they decrease with the more abstract patterns. In principle, a pattern description contains the elements (coresymbols): name, context/relation to other patterns,
problem description and a solution with a diagram
representing the structure of the solution.
The pattern collection of Gamma et al. [45] contains
23 design patterns which incorporate the experiences
with object-oriented software development and are
based on the pattern definition given above. Patterns
allow one to talk about ’stable’ properties of solutions
as they provide a common vocabulary and thus help to
find the appropriate communication level in contexts of
high complexity. The presented catalog of patterns with
their relationships among each other is not complete
in the sense of designing a complete application stepby-step and therefore does not represent a language.
The pattern description is subdivided in 13 categories
including these of Alexander and is enlarged with
technical hints and details.
Buschmann et al. [33] distinguish three kinds of
patterns: at the highest level we find architectural
patterns, the medial level contains design patterns and
at the bottom we have the programming language
dependent idioms. This system of patterns allows one
to refine a larger pattern by smaller patterns as well
as to combine patterns of the same level of abstraction
with each other. But this system lacks ’computationally
completeness’ in the previously described sense and
therefore does either not represent a pattern language
in the Alexandrian sense.
2.4. Construction of a CAS-pattern
In this section we introduce the general structure of a
CAS-pattern. It is constructed of the three theoretical
building blocks CAS, EA and conceptional patterns.
CAS-patterns are a way for identifying, describing
and analyzing real-world socio-technical systems that
behave in the sense of CAS theory. They are a means
to represent complex systems in a compact and unified
manner in order to grasp the essential parts as well
as to provide a common vocabulary for the research
community. A CAS-pattern consists of the following
general structure:
I) Name: the name of the pattern
II) Context: a description of appearing contexts and
relations to other CAS-patterns
III) Complexity: specification of complexity
’sources’ and discovered non-linearities
IV) Solution space: these ’singularities’ enfold together the solution of the pattern and have to be
understood in analogy to the hexagon metaphor
i) System and agents: description of system properties, levels of granularity and views of agents
ii) Rule set(s) / methodologies: used rule sets and/or
methodologies
iii) Emergent patterns: discovered emergent conceptual and non-conceptual patterns of the system at different levels of abstraction and their related feedback
mechanisms
iv) Evolution in time: history and dynamics of the
systems evolution
v) Technology: reused and developed technologies
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Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
vi) Symbolic interaction systems / languages: established symbol systems respectively languages for the
communication/interactions of the agents
After the description of the case study we show
the application of this CAS-pattern structure to our
empirical ’living object’.
3. Research approach
In order to explore the potential of CAS-patterns
for the identification, description and analysis of realexisting socio-technical systems, we applied the structure developed above to a case study of the semantic
standardization project in Germany over 3 years (20072009). The gained experiences guided our selection of
theory, and in turn, the CAS-pattern brought us a new
understanding of the phenomenon area.
Following the methodology of Eisenhardt [47] for
building theory from case study research, we gathered
data through interviews, workshops, review of documents and assistance in the development of system
components. The interviews lasted on average one hour
and happened regular with some key informants during
the 3 years. The workshops were topic oriented and
contained framework development, project meetings,
development of the GOS map, technological and organizational issues. We assisted, for example, in the
development of the model driven environment or the
monitoring of conformance.
In total, we inquired over 30 participants at different
levels of the system in order to gain a cross-sectional
dimension for the identification of the basic properties
and processes. The stakeholders belong to the groups
administration, IT-manufacturer, external experts and
service provider. For reasons of validation, we also
used information sources like websites, public reports
and internal notations.
As mentioned in the beginning of the theoretical
background section, we investigated for the identification of the core-symbols nearly 100 scientific publications in the context of complex adaptive systems
and enterprise architecture. With a similar motivation
like Pathak et al. [23] we undertook an in-depth examination of these articles to identify the core elements
of the theories.
4. Case study
Germany Online [48] is Germany’s national egovernment strategy of the federal government,
federal-state governments and municipal administrations. It aims for an integrated e-government system of
the different administrative levels by means of a uniform communication infrastructure (Germany Online
Infrastructure) and standardized data exchange formats
(Germany Online Standardization - GOS).
The e-government standardization project is managed by the Federal Ministry of the Interior and the
federal state of Bremen. The aims of the project are to
support and co-ordinate the development and provision
of standards for electronic data exchange.
The existing laws and especially the federal system
of Germany provide the federal-state and municipal
agencies with a high degree of autonomy in designing
and maintaining their IT-architecture and in making
their own IT investment decisions. These facts lead to
a complex IT landscape with proprietary implementations of software interfaces and bilateral agreements
on semantic meaning of the transferred data. To give
an insight into this scenery, imagine for example the
number of the 5400 civil registry offices equipped
with no less than 1000 different IT-systems, the 12000
municipal financial administrations with their countless
interfaces or upcoming implementations for the decentral electronic marital status registrations registry.
To establish interoperability between the agencies
GOS uses the approach of semantic standards based
on the UN/CEFACT-CoreComponent idea to unify
the communication interfaces through prescribing the
semantic meaning of the transferred data.
5. Application of the CAS-pattern
In this section we use the developed CAS-pattern
structure as our epistemological lens for the description
and analysis of the semantic standardization system in
Germany.
I) Name: Semantic standardization in Germany
II) Context: Achieving of semantic interoperability
within and with the public administration. As a core
pattern of interoperability we find manifold relations
to nearly all public service systems.
III) Complexity: As complexity ’sources’ for the
development of semantic standards we identified
• a heterogeneous network of numerous autonomous agents (see Fig. 2)
• valid model transformations based on naming and
design rules
• development of common meanings for core components
• foundation of developed standards through a ’legal interoperability’
• usage of incompatible XMI dialects
• scaling of the rule set
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Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
EU and other Country Agencies
register
part of
part of
Project
get
use
store
evaluate
use
Parastatal Agencies
Federal Agencies
based on
Conformance
Model Driven
Approach
Federal-State Agencies
use
Economic Agencies
develop
NGO Agencies
store
Core
Components
enact
enact
enact
prescribe
Municipal Agencies
Data
Conference
support
Map
Framework
develop
Agenda
perform
XRepository
Adjustment
Authority
develop
evaluate
technical aspects
methodological aspects
organizational aspects
develop
CITIZENS
Coordination
report
Figure 3. Germany Online Standardization pattern
Figure 2. The network of communicating agents
from a german e-government viewpoint (following
[20])
•
historical grown-up data stores with incompatible
semantic structures
A non-linearity of particular interest is the diachronic
transmission of information objects through time. From
the objects point-of-view only communication paths
exists, whose interfaces have to be dynamic enough to
’catch’ the external semantic and technological shifts
through time.
IV) Solution space: In order to come up with the
prescribed complexities the system brings the following ’singularities’ into being:
i) System and agents: The system evolved three
basic properties: development of technical artefacts,
binding specification of rules and quality management of results. It spans a continuum of granularity
levels starting with XML artefacts - UML models model transformation environment - project development methodology - project monitoring and political
decision processes. The agents consist primarily of
initiatives e.g. the projects, GOS groups (see Fig. 3)
and administrations.
ii) Rule set(s) / methodologies: The basic rule set
for the development of semantic standards is implemented through a methodological artifact called ’GOS
framework’ (see Fig. 3). Further used methodologies
are for example the UN/CEFACT Core Components
Technical Specification, the GOS UML-profile or the
GOS conformance check.
iii) Emergent patterns: We identified mainly four
emergent patterns of the system. The first conceptual
pattern is presented in Fig. 3. It shows the interplay
of shared concepts of the system on an aggregated
level. We identified 10 concepts with 23 relations.
It helped to identify missing links between concepts
Figure 4. Visualizations of the GOS map
(e.g. between MDA and XRepository) and relieved the
understanding of the system for internal and external
agents. The two concepts core components and conformance are in itself emergent conceptual patterns.
The core components library represents a common
shared meaning basis and is used in the modeling
of semantic standards. The conformance monitoring
allows projects to compare themselves in relation to
other projects. As a non-conceptual pattern we developed the GOS map shown in Fig. 4. It contains
360 documented communication interfaces collected
through online surveys. This emergent pattern reveals
parts of the real existing communication interfaces
and helps to identify new core components as well
as further standardization demands.
iv) Evolution in time: The system came into existence at the end of 2006. From the gained experiences was noted the need for changing/readjustment
of concepts. This resulted in unifying and optimizing different model transformation environments, the
simplification of the core component library and the
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Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
enhancement of the rule base.
v) Technology: Use of a tool chain for modeling,
transformation, validation and documentation of semantic standards based on UML 2.1, UML-profiles,
OCL-constraints and XSD schemata. The developed
artifacts are stored in a public online repository.
vi) Symbolic interaction systems / languages: The
developed core components contain german attribute
names due to legal restrictions. For the development
of semantic standards, the use of UML is obligatory.
6. Discussion and current work
Model Driven
Approach
use
Project
use
Framework
develop
part of
provide
Community
use
use
supports
provide
provide
Map
Core
Components
stored
Repository
technical aspects
The presented CAS-pattern is a valid means for the
investigation of socio-technical systems, if it satisfies
the three conditions feasibility, correctness and usefulness (first mentioned by [49]).
For reasons of feasibility, the CAS-pattern is derived
from three well-established theories, which all are concerned with the same object of investigation, namely
systems. Therefore, the CAS-pattern incorporates logical consistent ’modes of thought’; they don’t belong
to different epistemological realms, like religion or art.
We could capture the essential elements needed to
describe socio-technical systems in the sense of CAS
in our case and therefore evaluate the CAS-pattern as
correct within the context of our objective. If we, for
example, had ’forgotten’ the agents of the system to be
an element of our CAS-pattern, we would have missed
a central aspect of the investigated phenomenon area.
Missing aspects can be discovered by experience or
by derivations from well-established theories, where a
missing aspect is essential.
We investigated its usefulness in interviews and
workshops as we presented the application of the CASpattern (including the emergent patterns) to the case
study. We received the response of the involved agents,
that the applied CAS-pattern allows to gain a different
view of familiar structures and noted that they started
to rethink future activities. In short, it was regarded as
an enrichment for their daily work.
In addition to findings of the practical usefulness, we
derived, on a scientific level new generic insights into
the development of semantic standards (see Fig. 5).
We recommend this generic pattern as a blueprint for
the work at the UN/CEFACT Standards Development
Reference Framework. Currently, we work on the integration of the UN/CEFACT’s modeling methodology
(UMM) [50] into the presented semantic standardization project. We will validate the derived generic
pattern against upcoming requirements and adjust the
CAS-pattern Semantic standardization in Germany in
response to new complexities and used methodologies.
method. aspects
organizational aspects
Figure 5. A generic pattern for semantic standardization systems
Nevertheless, the evaluation of the framework won’t
come to an end, since every case will have its own
specifics to be adapted in our approach.
7. Conclusion
In this paper we used the theories of CAS, EA and
patterns as building blocks for the construction of a
CAS-pattern for real-world socio-technical systems in
the context of e-government. CAS theory is a new
paradigm for a bottom-up conception of systems with
emergent behavior based on interactions of elements.
EA theory provides top-down principles for the creation of architectures in socio-technical systems. In
the next step we utilized the idea of the interwoven
aspects of the EA-hexagon inside the solution space
of the CAS-pattern. Thus, we incorporated into a
CAS-pattern a double movement of emergent and
reductionistic principles to grasp, via this unity, the
complexity of real-world systems. Pattern theory offers
the possibility to structure complex phenomena in a
compact and unified manner and provide a common
vocabulary for the research community. A CAS-pattern
can be defined, compared to Alexander [44], as a threepart structure, which expresses a relation between a
context, observed complexities and a solution space.
As an epistemological lens, a CAS-pattern provides
a means for the identification, description and analysis of systems that behave in the sense of CAS.
It coherently incorporates three formerly autonomous
’modes of thinking’ that can guide scientists as well as
practicers in their understanding of real-world sociotechnical systems. It provides
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Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
•
•
•
•
•
•
•
an anthropological and epistemological foundation of core-symbol functions,
through the incorporated ’modes of thought’, a
coherent and different ’view’ at the empirical data,
a classification of CAS-pattern,
a multi-disciplinary approach, since it can be
used by different disciplines concerned in sociotechnical systems research,
a means to find out, why systems don’t behave
in correspond to CAS and how to identify the
barriers and possible parameters to change,
an achievement of larger patterns by smaller ones
in the sense of Alexander and
in our opinion the potential of a paradigm shift in
the Kuhnian sense.
The presented approach should be understood as
a starting point of discussion, the first of necessary
iterative studies. The authors hope to be helpful in
the communication of an idea dawning on the horizon.
The CAS-pattern is in certain aspects free in its structure, insofar as the core-symbols and their relations
aren’t ’hard wired’, but allow for, and require changes.
We think the presented theories are essential for this
approach, but not limited to it. The identified coresymbols are derived from scientific publications, but
lack a broader discussion or semi-automated foundation. We will now investigate, in a next step, the
analysis of scientific publications through semantic
algorithms to justify our inter-subjectiv gained terminological basis. Further limitations affect the nested
behavior of CAS, a missing coherent symbol theory
and the participation of the systems agents in the
development of the CAS-pattern.
The next logical step is to apply the CAS-pattern to
other phenomenon areas in order to develop a CASpattern language. This kind of language would be an
approach to building up global CAS in the Alexandrian
sense based on a common vocabulary - and maybe a
possible way to answer the simple question of: can we
all ’govern’ a planet?
References
[1] K. Kosanke, “ISO Standards for Interoperability: a
Comparison,” in Interoperability of Enterprise Software and Applications: INTEROP-ESA’05, First International Conference on Interoperability of Enterprise
Software and Applications, 2005.
[2] D. Chen, G. Doumeingts, and F. Vernadat, “Architectures for enterprise integration and interoperability: Past, present and future,” Computers in Industry,
vol. 59, no. 7, pp. 647–659, 2008.
[3] B. D. Rukanova and R. A. Stegwee, “Identification of
different types of standards for domain-specific interoperability,” in MIS Quarterly Special Issue Workshop
on: Standard Making: A Critical Research Frontier for
Information Systems Seattle, 2003.
[4] UNDP, “e-government interoperability: Overview,”
United Nations Development Programme Regional
Centre in Bangkok, Tech. Rep., 2007.
[5] E. Cassirer, An essay on man. Double Anchor Books,
Garden City, New York, 1954.
[6] M. Friedman, “Ernst cassirer,” in The Stanford Encyclopedia of Philosophy, fall 2008 ed., E. N. Zalta, Ed.,
2008.
[7] P. Berger and T. Luckmann, The social construction of
reality. Doubleday New York, 1967.
[8] M. Walzer, Thick and thin: Moral argument at home
and abroad. University of notre dame Press, 1994.
[9] T. S. Kuhn, The structure of scientific revolutions.
University of Chicago Press Chicago, 1962.
[10] W. Buckley, Society as a complex adaptive system.
W. Buckley (ed.), Modern Systems Research for the
Behavioral Scientist, 1968.
[11] J. H. Holland, Hidden order: How adaptation builds
complexity. Addison Wesley, Reading, MA, 1996.
[12] ——, Emergence: From chaos to order.
Books, 1998.
Perseus
[13] M. Gell-Mann, “Complex adaptive systems,” Complexity: metaphors, models, and reality, vol. 19, pp. 17–45,
1994.
[14] S. Kauffman, The origins of order, self-organization
and selection in evolution. Oxford University. New
York., 1993.
[15] ——, At home in the universe: The search for laws of
self-organization and complexity. Oxford University
Press, USA, 1995.
[16] T. Choi, K. Dooley, and M. Rungtusanatham, “Supply
networks and complex adaptive systems: control versus emergence,” Journal of Operations Management,
vol. 19, no. 3, pp. 351–366, 2001.
[17] A. Desai, “Adaptive complex enterprises,” Communications of the ACM, vol. 48, no. 4, pp. 32–35, 2005.
[18] M. Rhodes and G. MacKechnie, “Understanding public
service systems: Is there a role for complex adaptive
systems theory?” Emergence, vol. 5, no. 4, pp. 57–85,
2003.
[19] P. Zhou, “Planning E-Government As Complex Adaptive System,” in Wireless Communications, Networking
and Mobile Computing, 2008. WiCOM’08. 4th International Conference on, 2008, pp. 1–4.
9
Proceedings of the 43rd Hawaii International Conference on System Sciences - 2010
[20] M. Janssen and G. Kuk, “A complex adaptive system perspective of enterprise architecture in electronic
government,” in Hawaii International Conference on
System Sciences, vol. 39. IEEE, 2006, p. 71.
[36] D. J. Nightingale and D. H. Rhodes, “Enterprise systems architecting: Emerging art and science within
engineering systems,” MIT Engineering Systems Symposium, March 2004, 2004.
[21] Y. Merali and B. McKelvey, Complexity and information systems: the emergent domain. Palgrave Macmillan, 2006.
[37] C. M. Pereira and P. Sousa, “A method to define an
enterprise architecture using the zachman framework,”
ACM Symposium on Applied Computing (SAC ’04),
March 14-17, 2004, Nicosia, Cyprus, pp. S. 1366–1371,
2004.
[22] V. Grimm et al., “Pattern-oriented modeling of agentbased complex systems: lessons from ecology,” Science, vol. 310, no. 5750, pp. 987–991, 2005.
[23] S. Pathak et al., “Complexity and Adaptivity in Supply
Networks: Building Supply Network Theory Using
a Complex Adaptive Systems Perspective*,” Decision
Sciences, vol. 38, no. 4, pp. 547–580, 2007.
[24] J. Fromm, The emergence of complexity. Kassel Univ.
Press, 2004.
[25] J. Sutherland and W. van den Heuvel, “Enterprise
application integration and complex adaptive systems,”
Communications of the ACM, vol. 45, no. 10, pp. 59–
64, 2002.
[26] P. Anderson, “Complexity theory and organization science,” Organization Science, pp. 216–232, 1999.
[27] T. Lenton and M. van Oijen, “Gaia as a complex adaptive system,” Philosophical Transactions: Biological
Sciences, vol. 357, no. 1421, pp. 683–695, 2002.
[28] J. DeRosa and L. McCaughin, “Combined Systems
Engineering and Management in the Evolution of Complex Adaptive Systems,” in Systems Conference, 2007
1st Annual IEEE, 2007, pp. 1–8.
[29] N. Goodman, Languages of Art: An Approach to a
Theory of Symbols. Indianapolis: Bobbs-Merrill, 1968.
[30] L. Steels, “Language as a complex adaptive system,”
Lecture notes in computer science, pp. 17–28, 2000.
[31] F. Lillehagen and D. Karlsen, “Enterprise architectures
– survey of practices and initiatives,” 2005.
[32] M. Rohloff, “Enterprise architecture – framework and
methodology for the design of architectures in the
large,” European Conference on Information Systems,
2005.
[33] F. Buschmann et al., “Pattern-oriented software architecture: a system of patterns.” John Wiley and Sons.
New York, 1996.
[34] K. Harmon, “The ’systems’ nature of enterprise architecture,” IEEE International Conference on Systems,
Man and Cybernetics, 2005, 2005.
[35] R. Evernden and E. Evernden, “Third-generation information architure,” Communications of The ACM March
2003/Vol. 46, No. 3, pp. S. 95–98, 2003.
[38] A. Wegmann, “The systemic enterprise architecture
methodology (seam) - business and it alignment for
competitveness,” Published at the International Conference on Enterprise Information Systems 2003 (ICEIS
2003), 2003.
[39] H. Jonkers et al., “Towards a language for coherent
enterprise architecture description,” in M. Steen and
B.R. Bryant (eds.), Proceedings 7th IEEE International
Enterprise Distributed Object Computing Conference
(EDOC 2003), 2003.
[40] D. Dreyfus and I. Bala, “Enterprise architecture: A
social network perspective,” Proceedings of the 39th
Hawaii International Conference on System Sciences 2006, 2006.
[41] P. Saha, “Analyzing the open group architecture framework from the geram perspective,” Institute of Systems
Science, National University of Singapore, China, 2003.
[42] ISO 15704, “Industrial automation systems - requirements for enterprise reference architectures and
methodologies,” 2000.
[43] D. Senghaas, “The Civilization of Conflict: Constructive Pacifism as a Guiding Notion for Conflict Transformation’,” Berghof Handbook for Conflict Transformation, pp. 29–07, 2005.
[44] C. Alexander, The Timeless Way of Building.
University Press, 1979.
Oxford
[45] E. Gamma, R. Helm, R. Johnson, and J. Vlissides,
Design patterns: elements of reusable object-oriented
software, 1995.
[46] C. Alexander, S. Ishikawa, and M. Silverstein, A Pattern Language - Towns Buildings Construction. Oxford University Press, 1977.
[47] K. Eisenhardt, “Building theories from case study research,” Academy of management review, pp. 532–550,
1989.
[48] Deutschland Online Standardisierung. [Online]. Available: http://www.standardisierung.deutschland-online.
de/
[49] H. Hertz and H. von Helmholtz, Die Prinzipien der
Mechanik. JA Barth, Leipzig, 1894.
[50] P. Liegl, R. Schuster, and M. Zapletal, UN/CEFACTS’s
Modeling Methodology (UMM) 1.0 - A Guide to UMM
and the UMM Add-In, 2008.
10