Towards Devising an Architectural Framework for Enterprise

Operating Systems

Sérgio Guerreiro

, Steven van Kervel

and Eduard Babkin

Universidade Lusófona de Humanidades e Tecnologias, Escola de Comunicação, Artes, Arquitetura e Tecnologias da

Informação, Campo Grande, 376, 1749-024, Lisbon, Portugal

Formetis BV, Hemelrijk 12 C, 5281PS Boxtel, Netherlands

National Research University Higher School of Economics, B. Pechorskaya 25/12, Nizhny Novgorod, 603155, Russia

Keywords: Control, DEMO, Enterprise Engineering, Framework, Generation, Operating System.

Abstract: One often observes that despite the efforts involved on information systems development, many times the

achieved solutions do not comply well with the needs of the organization and lack in change agility to face

new emerging requirements. This paper conceptualizes about an architectural framework specifically

designed for explaining and representing the working environment of enterprise operating systems (EOS)

and non-EOS information systems (IS) that depend on it. With these concerns in mind, the goal of EOS is to

capture and control all phenomena that occur in an organization and then to provide all the required data for

all IS for that organization. Using a computer engineering metaphor, this paper defines the theoretical

foundations, and the methodology to design and implement an operating system for organizations. To

achieve this, EOS is a model-driven dynamically. The models are based on domain ontology with C4-ness

qualities and expressed in ontological language. It will be shown that the theory of enterprise ontology and

the DEMO methodology provide a high degree of ontological appropriateness for this domain. This paper,

outline a framework with its foundations, concepts, principles and stratification of IS, which is a radical new

approach, useful to discussion this solution among the practitioners. A methodology to apply this

architectural framework is discussed using a professional production case management.

1 INTRODUCTION

Much similar to explosion of design space after

introduction of reinforced concrete into the practice

of civil engineering, deep penetration of Information

and Communication Technologies (ICT) into our

everyday activities leads to enormous inflation of

design possibilities of software architects and

engineers during design and implementation of

complex software and hardware artifacts which are

usually called information systems. This unwanted

and inflated design space leads to unmanageable

complexity in design and results in bad engineering.

Now there is a great demand to produce mental

techniques and tools, which will make design and

development of information systems intellectually

manageable.

Various proposals were offered to aim such goal,

which are called architectural frameworks. The main

purpose of architectural frameworks is to offer such

architectural principles, which curb this unwanted

design freedom as much as possible, but in such a

way, that good engineering is supported as much as

possible.

To the moment, there are plenty of architectural

frameworks in use. Some of them like TOGAF,

MODAF (Open Group, 2011) (Ministry Defense,

2010) encompass not only ICT aspects, and they are

actively applied for engineering of enterprises as a

whole. Despite a high level of conceptualization

achieved in these frameworks researchers (Dietz,

2006) argued serious critical statements (Teka et al.,

2012). For example, all of the mentioned

frameworks lack consistent definition of the key

concept of architecture, mixing in the same concept

high-level design principles and reusable design

constraints.

In our research, we reduce ambiguity in

definitions of architecture following a strict

definition of architecture (Hoogervorst, 2004),

which defines it as “a consistent set of design

principles and standards that guide design”.

578

Guerreiro S., van Kervel S. and Babkin E..

Towards Devising an Architectural Framework for Enterprise Operating Systems.

DOI: 10.5220/0004597805780585

In Proceedings of the 8th International Joint Conference on Software Technologies (ICSOFT-PT-2013), pages 578-585

ISBN: 978-989-8565-68-6

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

However, even in that case, we claim, that there are

other principal drawbacks in current theory and

practice of architecture for information systems.

Known approaches: (1) do not take into account

human-centric foundations of enterprises for which

the information systems are produced; (2) at the

same time they insufficiently use generic and

reusable formal methods and practices of

engineering sciences (for example, clear distinction

between function-construction perspectives, support

for design- and life-cycles); (3) they do not take into

account immanent stratification of abstraction levels

of information systems, if we consider them in the

global scope of the enterprise. The later drawback

has great influence if we take maturity and strategy

of particular enterprise during engineering of

information systems seriously.

In this work, we propose several foundational

concepts, which can be used for creating a radically

new kind of architectural framework, which focuses

on engineering of information systems, but

simultaneously takes into account critical issues of

Enterprise Engineering (EE) (Dietz and

Hoogervorst, 2012).

Our conceptualization is based upon

stratification of the various kinds of information

systems. Traditional Information Technologies

Systems (IT-S) occupy the bottom level of our

classification. Above the notion of IT-S we put a

stratification layer for the significant notion of

Information Systems (IS) which refers to systems

that capture some part or some aspect of the

enterprise in a truthful and appropriate way. The

third layer of stratification consists of Enterprise

Information Systems (EIS), which specify systems

capturing the enterprise as a group of individuals

that cooperate to achieve some common goal, a

product or service for a customer. It appears that

Enterprise Information System gives a practical

opportunity to integrate common IT concepts and

intrinsic characteristics of human being (like

responsibility, authority, sincerity and

competencies). The fourth level is the new concept

of Enterprise Operating system (EOS), an EIS,

which controls the business transactions operation in

an organization. Using a computer engineering

metaphor, this paper defines the theoretical

foundations, and the methodology to design and

implement an operating system for organizations.

Hence, the EOS controls the human enterprise in a

prescriptive way (similar to workflow) and provides

all atomic data to the information system that run on

top of this EOS.

From a theoretical perspective, to specify some

phenomenon in the world of phenomena using an

ontology we need a conceptual language. Therefore,

the proposed architectural framework is intended to

design and implement EOS, considering the

following aspects, which constrain the design space

of EOS:

1.Epistemological foundations.

2.Ontological foundations.

3.Enterprise Modelling.

4.Software Development.

In order to prove relevance and consistency among

all four aspects we propose to apply the concept of

C4-ness (Dietz, 2006). In our case it means that, the

proposed framework uses minimal, but complete,

number of concepts, which cover principal aspects

of EOS development.

In this framework, as any other engineering

domain, we use models. We define a model here as a

formal specification of some system that is being

used to study some other system. For EE we study

social systems (Dietz and Hoogervorst, 2012). This

applies for the defined information systems, IS's,

EIS's and EOS's that capture some domain of the

world of phenomena. Within that domain, there is a

specific phenomenon or aspect, which must be

represented by a specific formal model. The term

'formal' refers to the representation of a model in a

formal language and rules out any informal

illustrations, such as boxes and arrows or ambiguous

natural language.

In addition to the functional definition of a

model, - a model represents a system to study some

other independent system -, there are two commonly

used meanings of the term `model` in general

parlance. The first is that a model is a

conceptualization of a phenomenon in some domain

in the real world; a model references objects in the

real world. The second meaning is the use of the

term `model` also for a formal representation, a

specification S, expressed using symbols and their

relations in a formal language. If the modeling

language is being used for software generation then

the terms 'software primitive' and 'software

construct' are also being used often. Though the use

of the term 'model' for a conceptualization and for a

symbolic specification S may be potentially

confusing, it is clear from the context what is meant.

To capture some domain in the world of phenomena

in a truthful and appropriate way we need an

ontology (Dietz and Hoogervorst, 2012). To specify

models in a language we need conceptual languages.

The notions of ontology, conceptual languages,

models expressed in conceptual languages and the

TowardsDevisinganArchitecturalFrameworkforEnterpriseOperatingSystems

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Figure 1: The GSDP-MDE framework (simplified), derived from Guizzardi's framework.

quality of models, related to phenomena in the real

world, are closely related.

The Generic Systems Development Process

(GSDP) (Dietz, 2006) approach for engineering of

systems of any kind is compliant with the

technological theories for designing and

implementing things (Dietz and Hoogervorst, 2012).

The GSDP is a generic model for developing any

kind of artifact, including software systems, and is

followed here. In (Van Kervel,2012) is described

how the GSDP applied to software engineering,

using the Guizzardi framework, provides the

Generic Systems Development Process for Model

Driven Engineering (GSDP-MDE) framework for a

model-instance driven software engine, a simplified

version shown in Fig. 1.

The Guizzardi framework is extended with a

software engine E, with systems ontology. The

ontology C is the Using System (US) ontology of the

GSDP framework, in our case Enterprise Ontology.

The ontology C captures the real world in a truthful

and appropriate way and provides models with C4-

ness qualities. We design a modeling language L

with a meta model (software primitives and software

constructs) that is isomorphic to the ontology C. In

this way any models expressed in L offer the

advantages mentioned before. We may design a

model executing software engine of which the

systems ontology is isomorphic to the meta-model of

L (and the ontology C).

We present the approach to devising the

architectural framework for EOS as follows. In

Section 2, we introduce the detailed conceptual

structure of the proposed framework. In Section 3

describes the professional production case of

application of the proposed architectural principles

to development of complex information systems.

Finally, we discuss the results of research and make

a conclusion in Section 4.

2 DESCRIPTION OF THE

PROPOSED FRAMEWORK

This section describes the framework for the

enterprise operating system using textual

explanations and the conceptual map depicted in

Fig. 2. The definitions are divided into 3 clusters: (i)

scientific solution grounding, (ii) solution enterprise

environment and (iii) core solution. The aim of

presenting these definitions is to ease the

communication and discussion between the EE

researchers and practitioners / engineers. A formal

ontology using DEMO is expected to be further

developed accordingly with the ongoing research

activities of this proposal. At this point, it represents

the knowledge acquired by the research team and

configures the mandatory set of definitions to

explain its scope and goals.

Regarding the scientific solution grounding the

following definitions are, Architectural framework

(Greefhorst and Proper, 2011), Epistemological

foundations, Ontological foundations (Dietz, 2006),

Enterprise Modeling methodology, Software

Development of EIS and Model Driven

Environment (Kent, 2002); (Schmidt, 2006).

In the proposed architectural framework we wish

to explicitly introduce stratification among the

different kinds of information systems of modern

organizations. Such stratification facilitates

systematic assessment of information assets of the

organization, as well as helps in determining such

strategy development, which correlates with a

current level of IT-maturity. The definitions related

with the solution enterprise environment aims at

locating the scope and context where this proposal is

applicable. The proposed definitions of recognized

types of information systems are:

Information Technology System (IT) – is the

whole body of systems to get computers doing

something, not specifying some functional purpose

in the "world of phenomena". It encompasses, for

instance, disc drives, operating systems, languages,

databases. It encompasses systems that fulfill a

functional purpose within this scope.

Information System (IS) - refers to systems, built

on IT systems, which capture in a truthful and

appropriate way some part of the “world of

phenomena”. In most cases, IS's are known in the

form of Management information systems (MIS)

Software

engine

MDE

approach

Modeling

Language

truthfulness &

appropriateness

qualities

C4-ness quality

model specifications

Ontology

Conceptualization

Real World

Phenomena

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580

Figure 2: Framework overview. The definitions to operate EOS are inside the box in the right side. In the left side, are the

concepts related with EOS solution grounding.

(Laudon and Laudon, 2012). In our case

organizations, social systems that operate in a part of

the world of phenomena are of specific interest.

Since organizations, companies, legal entities etc.,

are complex entities with many different appropriate

views (finance, personnel, inventory, etc), typically

many different IS's are needed to capture an

organization well. The term ‘truthful’ refers to the

requirement that the representation provided by the

IS is at any point in time, completely and in detail,

true. The term ‘appropriate’ refers to a functional

quality; the requirement that the IS should support

the enterprise and its stakeholders well and in a

useful way. IS's may capture also dynamic

phenomena, phenomena that exhibit state transitions

within a defined and allowed discrete state space

must be represented in a truthful way. In practice,

such dynamic phenomena represent agile

enterprises; we observe in general that these

phenomena evolve over time in a unpredictable way.

To meet definitions, IS's should evolve also

smoothly over time in such a way that the evolving

phenomenon of agile enterprise is always captured

in a truthful and appropriate way.

IT and IS relationship has significant importance.

Actually, by the literature review it is consensual

that enterprises require alignment between its IT

systems and the business definition (Hoogervorst,

2009) whereas this alignment demands the

consideration of aspects such as human,

organizational, informational and technological

(Mulder, 2007). In line, a well-known industrial

standard: Archimate 2.0 (Open Group, 2013) uses

three core aspects to model and align the enterprise:

(i) the business architecture, (ii) the Information

Systems (IS) architecture and (iii) Information

Technology (IT) architecture. IS are defined by

(Laudon and Laudon, 2012) as a set of interrelated

components that collect (or retrieve), process, store,

and distribute information to support decision-

making and control in an organization. In addition,

IS’s may also help managers and workers analyze

problems, visualize complex subjects, and create

new products. On the other hand, IT systems are

referred in (Laudon and Laudon, 2012) by the set of

hardware, software, database, networking along with



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the tools and techniques for security and control,

existing in the enterprise. Hence, a clear conceptual

separation is understood in the literature regarding

IS and IT. However, IS and IT are related because IS

is built using IT and strictly depends on it.

Enterprise Information System (EIS) - refers to

systems, built on IS's, that capture specifically an

enterprise. An enterprise is defined as a social

system, a group of human individuals – actors - that

cooperate and communicate to achieve some

common goal, a product or service for an external

customer (Dietz and Hoogervorst, 2012). This

definition is narrower than the notion of an

organization, for example a company, with

production facilities, bookkeeping etc. The notions

of enterprise, actors, communication and production

are precisely defined in the EE manifesto (Dietz and

Hoogervorst, 2012). EIS's provide two distinct

perspectives on an enterprise. The first is a

descriptive perspective that provides a complete,

detailed truthful representation of the operating

enterprise. Since enterprises exhibit a discrete

dynamic behavior, actors are communicating, there

are acts and facts, the states and state transitions that

have to be represented also. The second is a

prescriptive perspective. An EIS is based on a model

of the enterprise and prescribes the behavior of the

enterprise to act according to the model (Dietz,

2006). The EIS is a software engine that executes a

business transactions model instance; for each

specific production instance there is a specific model

instance under execution. An EIS prescribes,

enforces all actors of the enterprise to act, the so-

called communication acts (Dietz, 2006), within the

allowed state space and state transition space of the

model under execution. There is no possibility for

any actor to deliver communication acts outside the

allowed state space. This is called enforced

compliance of an enterprise to a model. The allowed

state space is defined by and calculated from the

business transaction models under execution. This

prescriptive capability is functionally equivalent to

state of the art workflow systems; there is enforced

compliance of all actors to a model. Unlike state of

the art workflow systems, the workflow capability is

here calculated from the enterprise model under

execution, not specifically modelled. The purpose of

EIS's is to capture working, implemented enterprises

in full detail. To achieve this, the ontological model

of the enterprise is – after validation and acceptance

by the stakeholders – extended with all relevant

info-logical and data-logical transactions. This

modeling process is called fine-grained business

transactions modeling and is an implementation of

an ontological model. There are typically more

possible implementations of an ontological business

transaction model and finding the optimal

implementation for a specific enterprise is an

important process. The support of business

transaction is DEMO (Dietz, 2006), which is a

model under execution that provides a complete,

detailed truthful representation, including the current

state, of the operating enterprise.

Enterprise Operating System (EOS) -

encompasses an EIS, a software engine that executes

a (fine-grained) DEMO model and in addition (to an

EIS) provides support for all non-EIS IS's in an

organization, company, entity etc. In software

engineering an operating system of a computer

system monitors and controls all hardware

subsystems and provides a generic, abstracted and

hardware independent interface to the subsystems

for all software applications. Similarly, an EOS

captures and controls (Guerreiro et al., 2012) all

phenomena in an enterprise and provides all required

data for all IS's for that organization.

The theory of enterprise ontology, EO, the operation

axiom (Dietz, 2006), specifies three worlds of an

organization; the A-world of actors, the C-world of

communication between actors, and the P-world of

productions. An EIS provides – as described before

– control of all communication acts, which is the C-

world, for all actors, which is the A-world. The

theory of EO captures also the P-world of

productions; the composition axiom specifies the

hierarchical structure and the aggregation of

productions that are performed by specific actors.

DEMO models define the productions and those

actors with their communication acts about their

productions. The actual production, the so-called

production facts, is explicitly not executed by an

EIS; only the sequence of the production facts is

controlled. If an IS is required for specific

production facts, for example the calculation of

some specific data, or the measurement of quality,

then an independent IS, specifically designed for

that purpose, is needed. The operation of these

production oriented IS's is however monitored and

controlled by the EOS. An EOS controls and

monitors all atomic elementary communication and

production acts and facts (which is the EIS

capability). An EOS has “total factual knowledge”

about “anything that is controllable, until the finest

details, that happens in the enterprise”. An EOS

therefore provides the perfect bridge between the

organization as phenomenon in the real world and

all IS's that capture some aspect or view of that

organization (finance, inventory control, personnel

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information etc).

Adaptive Case Management Systems (ACMS) –

as one of many different kinds of IS’s for production

systems, ACMS's are a combination of an EOS and

one or more (non-EIS) IS's, supported by the EOS,

that capture together some parts of an operating

organization. The EOS captures, as described

already before, the operation of the enterprise. The

operation of the enterprise involves the actors, their

communication, all precisely specified, enforcing

compliance to the enterprise model being executed.

The IS's for ACMS's are typically document-

oriented production environments, for the creation of

documents, forms, decisions, datasets from legacy

applications, etc. ACM's are typically aimed at the

production of services, where the customer of the

organization is an active co-producer. The services

are tailor-made and adapted to the needs and

requirements of the customer, as opposed to mass

production. The production is subjected to so-called

business rules derived from legal regulations,

contracts etc.

Almost all defined kinds of systems in our

framework represent complex socio-technical

systems where involvement of human factors is

highly influential. Many analysts and system

thinkers argued that for achieving the design goals

of such systems developers need much more higher

levels of epistemological truth guarantors in

comparison with traditional technical systems

(rephrase of the words by Eric Maskin, Nobel Prize

Laureate in Economics Design). Including into the

proposed framework several hierarchically

structured foundations reflects this aspect. In our

particular case, we suggest to narrow a generic

concept of guarantor towards specific definition of

C4-guarantor. Further, in Section 3 we will describe

in details the proposed principles.

Notion and interrelations of these foundations

correspond to the core principles of inquiring

systems design by (Churchman, 1971).

Epistemological foundations are needed to align and

verify IS, EIS and EOS solutions with expectations,

values and norms of enterprise stakeholders. In the

particular case of our framework, we offer to use the

(Habermas, 1984) (Habermas, 1987) theory of

communicative action. Ontological foundations

determine cornerstone concepts of IS, EIS and EOS

which can be treated as meta-models. As ontological

foundations we suggest to exploit the PSI-theory of

Enterprise Ontology by J. Dietz (Dietz, 2006) which

is tightly connected with the chosen epistemological

foundations of (Habermas, 1984) (Habermas, 1987).

In own turn, Enterprise Modeling aspect determines

concrete stages and outcomes which comprise

concise and coherent description of all relevant parts

of IS, EIS and EOS. On that stage, we suggest to use

in our framework such modeling methodology as

DEMO (Dietz, 2006) for which Enterprise Ontology

naturally becomes a truth guarantor.

The major part in the framework is the

architectural aspect of Software Development,

which determines generic requirements and shapes

how executable software artefacts can be produced

on the basis of the enterprise models. To elaborate

that aspect we propose to revise too generic OMG

principles of model-driven design and development

and replace them by the GSDP-MDE methodology

(Van Kervel, 2012) (Van Kervel et al.,

2012)supported by a number of specialized system

components. The components include (1) run-time

executor of DEMO models; (2) run-time rule

executing engine; (3) Control component; (4) Policy

enforcement component; (5) Argumentation and

collective work component. For each component we

propose to use the following architectural principles

and solution core definitions.

Operation – “the collective activity of the elements

in the composition and the environment is called the

operation of the system. Thus, one could also say

that the operation of a system is the manifestation of

its construction in the course of time. It encompasses

both the productions as performed by the elements

in the composition and the interactions through the

structural bonds. The operation of a system can be

described by specifying (for every element in the

composition) the action rules that guide or prescribe

the activity of the element” (Dietz, 2006).

Actor - specify a role who is responsible for each

part of the transaction, who initiates it and who

executes it (Dietz, 2006).

DEMO Business Transaction - follows the

definition given for a transaction in Enterprise

Ontology (Dietz, 2006), where a transaction is the

set of coordination acts that are performed as steps

in a universal pattern, always involving two actor

roles (the initiator and the executor) and are aimed at

achieving a particular result. Here the enterprise

models, by the mean of DEMO business transaction

models may capture much more than the strictly

ontological DEMO models that are fully

implementation independent

State Space and State Transition Space (C-world)

– The state space is the set of allowable states of a

system. The transition space is the set of allowable

sequences of transitions of a system. Every state

transition is only dependent on the actual state

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(Dietz, 2006).

Fine-grained Model – A model stands for the

definition given by (Apostel, 1960), where: “Any

subject using a system A that is neither directly nor

indirectly interacting with a system B, to obtain

information about the system B, is using A as a

model for B”. Fine-grained model stands for the

concern of specifying all the minor details in respect

to the stratification that is being considered at each

time, but using as starting point the ontological

models that have the advantage of being

implementation independent. In practise,

implementation is the extension of the

implementation-independent ontological model with

implementation-specific transactions and actors, also

called fine-grained modeling.

Observe (capture) Business Transactions – the

collection of steps and facts within DEMO business

transactions that actors are performing during

operation are observable. There are parts of a

business transaction that are observable, while others

are unobservable (Guerreiro et al., 2012). Hence, not

all the state space and transition space of the

enterprise is observable directly in the operation of

an enterprise.

3 ADAPTIVE CASE

MANAGEMENT SYSTEM:

PROFESSIONAL CASE STUDY

The first EOS, now in industrial production,

supports an adaptive case management system

(ACMS) for a Dutch semi-public company that

delivers energy and utility services, such as water

and electricity, for citizens. The complex tailor-

made contract for a specific individual customer

covers issues such as type of services provided,

costs, costs calculation methods, conditions for

payments, instructions for subcontractors,

correspondence etc. The contract should comply

with external legal regulations and internal business

policies, conditions, procedures. This compliance

should be enforced to the staff and its compliance

has to be proven for each individual customer and

contract for legal reasons. The quality of the

contracts should be high; errors are unacceptable,

incomplete transactions, deadlocks, deadline

overflow, violation of procedures etc, must be

eliminated. This is a very complex business process

with 33 production steps / transactions. The EOS

(Enterprise Operating System) executes fine-grained

DEMO models, enforces compliance to business

rules, and supports the ACMS. The ACMS is an IS

for the production and management of documents,

technical drawings, interfaces to legacy IT systems,

including an ERP production control system. The

contract contains documents originating from

various sources and several subcontractors.

The project started with DEMO modeling with

the knowledgeable staff, which delivered the so-

called ontological or essential DEMO model of the

enterprise. Extensive shared reasoning with the staff

has been done to validate that this ontological

DEMO model implements properly the service of

the enterprise delivered to the customer. The second

step involved a fine-grained DEMO modeling step,

starting from the ontological DEMO model, to

model the optimal detailed implementation of the

ontological model. The result is a DEMO model

with 33 ontological, 'infological' and 'datalogical'

transactions that has been subjected to extensive

simulations with the staff for acceptance. No

software programming was done yet. The accepted

DEMO model provides C4-ness quality

specifications for the ACMS. Specifically it

provided a constructional decomposition of the

ACMS with a high degree of granularity. The

ACMS consists of some 30 independent software

components with a minimized complexity and a

minimized interdependency. The C4-ness quality

specifications resulted in low efforts of software

implementation and good support of validation. The

acceptance of the ACMS was straightforward and

the functional quality, the business-IT alignment,

was found to be high.

This first case, in line with the proposed

framework, shows the technical feasibility of the

EOS for ACMS, applied for complex governmental

services, financial services etc. The design and

implementation of these type of IS's is highly

structured, systematic and provides good

opportunity to validate the business-IT alignment

before implementation of any software

programming.

4 CONCLUSIONS

In this work, a new conceptual structure of software

architectural framework is proposed. Such

framework allows reducing complexity and

ambiguity during engineering of several classes of

information systems. In particular, the framework is

expected for using during engineering of Enterprise

Operating systems (EOS). Authors argue that the

whole framework satisfies the C4 principles and

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follows the course of Enterprise Engineering. The

EOS controls and monitors all atomic elementary

communication and production acts and facts that

are observable, in order to assess the “world of

phenomena” occurring in the organization against

the predefined fine-grained enterprise models that

are consensual agreed between the stakeholders,

Using proposed architectural principles, we

envision continuing in developing a specific kind of

EOS, which has major characteristics of Adaptive

Case Management systems supported by the

requited architectural framework components. This

particular set of systems will be used to boot the

research of a Generic Systems Development for

Model-driven engineering (GSDP-MDE) of

Information systems. It is expected that the GSDP-

MDE help in eliminating ambiguity, absence of

anomalies, constructs overload and constructs

excess. In addition, we will seek alternative sets of

constraints for proposed aspects of our architectural

framework, for instance, full observation of business

transactions operation.

In our opinion, future results from this research

could be applied to other Information Systems

domains, since EOS conforms to a very consistent,

harmonious and congruent architectural framework.

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Laudon K. and Laudon J., 2012. Management Information

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D. Greefhorst and E. Proper, 2011. Architecture

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10.1007/978-3-642-20279-7_2, Springer-Verlag

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