Developing a Conceptual Framework to Structure an IT

Organization using an Ontology Engineering Methodology

Nelson Gama

, Lukasz Ostrowski

and Miguel Mira da Silva

Instituto Superior Técnico, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal

School of Computing, Dublin City University, Glasnevin, Dublin 9, Ireland

Keywords: IT Organization, Alignment, Conceptual Framework, Ontology Engineering Process, Concept Definition,

Concept Maps.

Abstract: Organizations are struggling to adopt practices that allow the best results trying to achieve alignment

between IT and an organization’s concepts and dimensions, pursuing efficiency and effectiveness.

Therefore, the structure of an IT organization is fundamental. However, despite the recognized importance

of IT organizational structure and the efforts made in the development of disparate perspectives and

relationships, no relevant references about its structure are found, and the existent ones are far from

satisfactory. There is neither a single framework nor one relating to what we consider to be relevant or

clearly dominant. This paper proposes the use of ontology engineering methodology to identify and

enumerate concepts and develop a conceptual framework in order to structure and establish a relationship

among concepts within an IT organization, which will allow the definition of an IT organization.

1 INTRODUCTION

Regardless of the type of organization, they all have

different concepts such as people, structure,

strategies, objectives, and approaches to Information

Technology (IT). The alignment between these

concepts, architectures and views is an imperative.

Considering that “having the right organization is

more important than having the right technology”

(Thompson, 2002), the pressure to define a perfect

alignment and the high inter-dependence between IT

and the organizations’ concepts increase, raising the

need to define the relationships able to meet these

demands (Zacarias et al., 2010). Moreover,

structures (such as a department, division,

directorate, etc.) and organizational concepts should

be defined to accommodate organizational needs and

IT. However, it is neither clear what the relevant

concepts are nor their relationships.

In the last years, organizations are struggling to

adopt the best approach, pursuing efficiency and

effectiveness in the alignment between IT and

organization’s concepts and dimensions.

Different proposals have been made to develop

the management of a system’s complexity and

deliver services, in accordance with an

organization’s strategies (Tiwana and Konsynski,

2010; Weill and Ross, 2004). Although there are

plenty of studies about IT structures (Cross et al.,

1997), no strong references on “how to” define an IT

Organization to be aligned with business strategy

and IT infrastructure were found. There is even less

documentation on restructuring IT Organizations in

research literature.

Due to the inexistence of approaches to structure

an IT organization (Gama et al., 2011), this paper

suggests ontology engineering methodology to

validate a conceptual framework as a proposal to

structure an IT organization and the concepts within

it.

This paper is organized as follows: “Related

Work” gives us the theoretical background and

“Research Methodology" presents the addressed

solution. Sample design is presented in section 4

and section 5 instantiates our proposal with two case

studies. Section 6 evaluates the proposal, followed

by “Conclusion”.

2 RELATED WORK

2.1 Ontology Definition

An ontology provides a foundation for

174

Gama N., Ostrowski L. and Mira da Silva M..

Developing a Conceptual Framework to Structure an IT Organization using an Ontology Engineering Methodology.

DOI: 10.5220/0004068501740179

In Proceedings of the International Conference on Data Communication Networking, e-Business and Optical Communication Systems (ICE-B-2012),

pages 174-179

ISBN: 978-989-8565-23-5

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

understandable knowledge, creating meaning;

aligning individuals and organizations through a

definition of concepts and simultaneously generating

new concepts while expanding existing ones (Dietz,

2006; Gama, et al., 2011). Usually ontology is

expressed by conceptual modelling grammars,

constituted by vocabulary plus meaning and

constructing a formal representation of interesting

areas (Dietz, 2006; Shanks et al., 2003). Besides the

ontological concepts reference, it is preferable to

have a graphical representation in which the

relationship is recognized among concepts (Gama, et

al., 2011; Zacarias, et al., 2010). To do this, we used

conceptual maps.

2.2 Concept Maps

Concept maps are graphical representations of

knowledge, namely of the concepts and relationships

between them (Novak and Cañas, 2008). Concept

maps are indicated to capture, represent, structure

and share tacit knowledge, in disparate domains, but

also to create new knowledge (Novak and Cañas,

2008). Beyond a knowledge representation, concept

maps are useful as an evaluation tool (Mintzes et al.,

2000). To construct a concept map, we begin with a

domain of knowledge, which diminishes difficulties

that arise in the origin of concepts. We should use an

“expert skeleton”, prepared by experts or

practitioners on a defined topic. This “expert

skeleton” concept map serves as a guide, an aid for

people with less knowledge in the domain to begin

(Novak and Cañas, 2008).

2.3 Organizational Theory

To understand organizations we should identify the

structure’s determining factors and influences, both

in the internal (technology, involving skills, tools,

applications, knowledge, and human resources) and

external environment (government, competitors,

suppliers and users). The organization’s structure,

based on functional division, aims at increasing

efficiency by combining functions and skills.

However, this functional division promotes the

presence of silos and misalignment within

organizations. On the one hand, strategy is a key

concept to consider in alignment efforts, since

different strategies require different structures

(Porter, 2008). On the other hand, internal

competencies ensure a defined strategy while

business processes guarantee the alignment between

strategy and customer’s needs (Gama et al., 2011).

2.4 IT Governance

IT Governance designates the internal mechanisms

developed by organizations to align IT with strategic

objectives and manage a system’s complexity (Weill

and Ross, 2004), focusing on decisions mechanisms

rather than on structuring (Haes et al., 2005).

However, effective IT Governance goes through a

combination of concepts, processes and relational

mechanisms (Haes et al., 2005) encompassing

frameworks with widespread use, of which one has

had major relevance: Enterprise Architecture

(Spewak and Hill, 1992; Zachman, 1987).

Nevertheless, IT Governance principles do not

offer a solution to our problem because they do not

provide any ideas on how to define and relate

disparate concepts within an organization. They do

reinforce that to enable IT Governance, we must

clarify concepts and their relationships.

2.5 Structuring an IT Organization

In our previous work (Gama et al., 2011), we

proposed a conceptual framework as an ontological

representation of a set of concepts within an

organization through a concept map. Our

contribution was to help making it clear that an IT

organization could not be a simple chart of units

from functional divisions. Instead, structuring an IT

Organization should reflect the requirements

necessary to align and meet needs and strategies.

However, the proposed framework remains untested

and the defined concepts have not been validated. As

Shanks stated (Shanks et al., 2003), the validation of

conceptual models is to generate quality, and a

suitable ontology can only make sense without

ambiguous semantics if its concepts are validated.

Moreover, we have already defined several

concepts that must be validated in accordance to a

methodology, avoiding ambiguity or omissions.

3 RESEARCH METHODOLOGY

3.1 Design Science Research

We follow Design Science Research (DSR) so as to

develop and validate the proposal to solve our

problem (Oates, 2006). DSR is a typical problem-

solving paradigm, addressing research through the

development and evaluation of designed solutions in

order to meet identified needs (Hevner et al., 2004).

Over a process with interactive steps, DSR is applied

according to two processes (March and Smith,

Developing a Conceptual Framework to Structure an IT Organization using an Ontology Engineering Methodology

175

1995): build and evaluate. In our proposal, the build

process corresponds to defining a conceptual

framework to structure an IT organization.

Both build and evaluate processes are composed

by two stages. In the first stage of the build process

we construct the domain definition and concepts

identification. This stage requires a construction

methodology. However, although DSR methodology

became widely mentioned, its methodology

guidelines are not clear or are rarely applied (Hevner

et al., 2004). In this context, we understand a

methodology as a collection of procedures to help

the development of a new or innovative idea.

3.2 Ontology Engineering Methodology

We use Ontology Engineering Methodology (OEM)

in the construct step (Ostrowski et al., 2012) using

conceptual maps. The OEM process, as illustrated in

Figure 1, is done through the collaboration of

practitioners from the same field and through

literature review (Ostrowski et al., 2012). Applying

this technique allows us to systematize a clear

methodology, with defined steps and procedures,

and to clarify knowledge before developing a

solution to an identified problem.

Figure 1: Simplified ontology engineering process

methodology applied [based on (Ostrowski et al., 2012)].

Following the OEM process, involving practitioners

from the IT department with disparate roles and

functions, we started by defining the domain, the

terms, their properties and purposes, identifying

limitations and evaluating possible constraints.

Thereafter, we created the concepts and determined

their relations to others concepts.

After this first step, we created and generated

(construct) concepts providing the ontological

vocabulary and symbols used to define a domain’s

problems and solutions (Hevner et al., 2004;

Vaishnavi and William Kuechler, 2007).

In the second step of the build process, we

present the concept maps relating concepts

graphically, as the meta-model of the conceptual

framework in “a set of propositions or statements

expressing relationship between constructs” (March

and Smith, 1995; Vaishnavi and William Kuechler,

2007).

In the evaluation process the construct is

demonstrated with a case study and then evaluated.

4 PROPOSAL

4.1 Domain Definition

We characterize an organization by defining the

domain of applicability and the boundaries of

influence. After, we proceeded to the definition of

the concepts through the ontology engineering

process. Our interest boundary is our internal

domain (Henderson and Venkatraman, 1993), as is

illustrated in Figure 2.

Figure 2: Boundaries of internal domain.

Internal domain involves organizational design

(including structure, roles, and relationships),

processes (defining organizational activities to

deliver product and services), and skills (which

indicate the organizational capabilities needed to

achieve the required organizational competencies).

Any organization exists to deliver a defined and

expected output to its users. We adopted the term

“user” to refer to the end point of an organization’s

service delivery. We differentiate and prioritize

users, considering and relating different criteria

(Martilla and James, 1977). Thus, one of the internal

domain interfaces is with users through services

delivered. Suppliers are another domain interface as

they deliver services to the organization. We

consider suppliers, government deliberations and

competitors concepts out of this paper’s scope

(Porter, 2008).

4.2 Concepts Definition

After identifying the internal domain, the next step is

the identification of key concepts applied to the

selected domain. These concepts should be listed

and the relationships between them established,

constructing a preliminary concept map. After a

preliminary map has been constructed, a revision is

needed in an iteration process, improving the map,

clarifying all structure and preparing the final map.

One of the very first concepts’ definitions should

be about the services delivered, the organization’s

output. The services supplied are the focal point of

business (defined by the strategy) and must be

understood by the users. They are defined as

Enumerate

terms

Define

properties

Identify

constraints

Create

concepts

Define

relations

Concept

maps

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business services which are decomposed into basic

services with elementary functionality (Kieninger et

al., 2011), as illustrated in Figure 3. A technical

service identifies what is required to support a

business service, avoiding the need to know users’

needs in detail.

Figure 3: Proposed conceptual framework.

Each technical service is supported by processes as a

sequence of value-added tasks performed by actors

and by the use or consumption of resources (Ko,

2009). We use processes modulation to identify

actors, skills, tasks, information, and applications. In

addition to providing a new cross-function way of

developing activities, process modulation allowed us

to involve people, receiving their contribution to a

process reengineering and optimization as well as

knowledge sharing. Each process is evaluated in

regard to how it is related to others.

An actor is an interventional resource, usually a

person or a team, with special skills that enable them

to fulfil tasks performing three kinds of actions:

management, development and maintenance (Dietz,

2006; Zacarias et al., 2010).

Tasks are the fundamental unit of work, usually a

job function, assigned to actors (individually or

grouped) (Oh and Park, 2003). Tasks are associated

to roles indicating the skills required to execute

them.

Roles define a set of tasks performed for a

defined organizational function that is accomplished

by the development of defined skills (Jeston and

Nelis, 2006; Oh and Park, 2003). A function can be

described by code (description), competence and

developed tasks.

Skills are a set of characteristics obtained from

the acquisition, training and development of

knowledge and abilities required to perform

assigned tasks (Henderson and Venkatraman, 1993).

Information, applications and technological

infrastructure refer to Enterprise Architecture

concepts. In our research we have used the work

around Enterprise Architecture, like an “expert

skeleton”, as a basis of our concept map (Lankhorst,

2009; Spewak and Hill, 1992): Information defines

the fundamental organization data in a relevant

organizational context, focusing on the required data

for technical services; Applications are the

fundamental set of software artefacts, services, and

components, needed to fulfil an organization’s

requirements; Technological infrastructure groups

equipment and hardware, providing the support to

applications and information as well as describing

the infrastructure.

Capability defines the capacity of an actor (group

or individual), with a distinctive set of skills and the

know-how to perform and create synergies (existent

or prospective) with value to the organization.

Capability can be described as: code, skills, and

tasks, among others (Ljungquist, 2007).

Competence is a “cross-functional integration

and co-ordination of capabilities” (Ljungquist, 2007)

provided by roles, which implies a quality inherent

to a cumulative hierarchy. Competence regards

development and improvement as a primary focus,

resulting from the combination of capabilities, skills

and roles.

An organizational chart refers to hierarchical

relations and vertical divisions based on a

combination of functions to organizational

optimization. It is a structure representation of roles

competencies, reporting relationships, hierarchic

levels and authority (Daft, 2004).

4.3 Conceptual Framework

A graphical representation outlines the conceptual

definition clarifying ambiguous semantics in the

model (Shanks et al., 2003). Therefore, a graphical

depiction of an ontological representation (Figure 3)

is a model (our conceptual framework) and models

are effective artefacts to support communication and

enable understanding (Zacarias et al., 2010).

The proposed conceptual framework uses the

ontological defined concepts, providing a model for

representing the real world through the relationship

among these concepts. The defined concepts should

be characterized with as many attributes as needed

in each organization.

5 DEMONSTRATION

To demonstrate and validate our proposal, we

applied it at the IT departments of two Portuguese

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public organizations.

In the first organization there were two different

departments with responsibilities related to IT that

did not fit their purposes: subjects were

simultaneously addressed to both departments; there

was misalignment between the departments and

between strategy and IT; users did not know which

department to contact to support issues; problems in

performance, communication, among others. To

better the service level, the organization improved

the IT departments’ coordination with our

conceptual framework in order to overcome the

above-mentioned problems.

In the other organization the problems were

related with misalignment between strategic

objectives, services provided, and IT support.

Without a clear definition of business services,

activities were developed within the defined

functions. Moreover, knowledge is rarely shared and

changes are barely discussed. There was a high

turnover rate of IT professionals leading to the loss

of specific knowledge and skills. To diminish

problems, a well-defined job description is needed,

clarifying the required skills to perform expected

tasks and accomplish the defined set of goals.

In both organizations, we started by sharing the

proposal’s framework with all personnel, edifying

the issues we wanted to address and the expected

benefits, involving and motivating people. We

identified the domain of interest and from terms

enumeration to concepts creation, we followed the

ontology engineering methodology. We populate a

single and shared common repository tool to support

all concepts and their relations. We used IBM

Rational System Architect as a repository tool and

our conceptual framework as the meta-model.

6 EVALUATION

We evaluated our proposal using a Conceptual

Model Quality Framework (Moody et al., 2003)

along three quality categories (syntactic, semantic

and pragmatic) and four components (domain,

interpretation, language, and model).

The model presented in Figure 3 is the endpoint

of the ontology engineering process. Along with it

we involved practitioners in the creation of concepts

from listed and enumerated terms. Therefore, the

expressed concepts and their relationships have

syntactic validity and provide the model’s validity

too. The followed methodology allows us to identify

all relevant terms and from them create our concepts

granting the model completeness. As the audience

was composed of practitioners, we can conclude its

pragmatic quality by the perfect interpretation.

Despite the quality validation of the model, it is our

intention to evaluate the proposed framework in a

wider group of practitioners from other

organizations. In the first case study we only

evaluated the proposal’s quality with the

practitioners involved in the project. In the second

one, we received criticism and contribution through

a provided questionnaire with questions about the

syntactic, semantic and pragmatic quality categories.

Moreover, we asked a group of eight professionals,

from four different organizational functions, to

separately identify concepts related to the IT

structure. After comparing the different proposals

with ours, we concluded that our proposal has high

quality. To the same professionals we gave our first

list of concepts, without relationships, and asked

them to establish those relationships, adding more

concepts if they thought needed. With them we

compared the different proposals against ours and, in

all cases, the people involved in this experiment

showed a preference for the quality of our proposal.

Therefore, we may conclude that the proposed

conceptual framework has both validity and quality.

7 CONCLUSIONS

We developed and evaluated a proposal framework

to structure an IT organization, using an ontology

engineering research methodology to define

concepts and relationships.

Our proposal to structure an IT organization ends

in a conceptual framework, which constitutes an

ontological reference. We propose a framework to

identify concepts as an organizational ontology. In

addition, our work can be used as an “expert

skeleton” to further develop or adopt in other

organizations.

Our goal was not to define ontological concepts,

since we use much of the available identified

concepts. Our main contribute was a conceptual

framework developed to provide a model that

enables definition and correlation between concepts

enabling us to structure an IT Organization.

The proposal framework shows the alignment

between concepts within an IT organization’s

internal boundary. Through the identification of

concepts, the conceptual framework establishes a

relationship among them in an ontological graphical

representation providing us a reference and, thus, the

end result is aligned with this goal.

Our future work aims at applying the conceptual

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framework in other contexts and organizations. It is

also our intention to present our work to other

practitioners to obtain critical enhancements in order

to improve the model and the development

methodology.

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