Introduction

All systems developers approach the development task with a number of explicit and implicit assumptions about, for example, the nature of human organizations, the nature of the design task, the value of technology, and what is expected of them. As was noted in chapter 2, these assumptions play a central role in guiding the information systems development process. They guide not only the definition of object systems, but also the preferred approach to inquiry, i.e. how the developers improve their understanding and knowledge about them. The assumptions can either be held by the system developers or be embedded in their preferred development approach. In either case they affect the designed and implemented system.

But in order to understand the relationship between assumptions and development approaches we need to elaborate on the notion of ‘paradigm’ and how it applies to ISD. An exploration of the philosophical assumptions underlying different methodologies and their tools is a prerequisite for a better understanding of the influence of philosophical attitudes on the practice of ISD. Groups of related assumptions about reality and knowledge are at the core of research paradigms. By introducing a general classification of the assumptions that characterize alternative research paradigms, this chapter provides the philosophical basis for the analysis of ISD and data modeling in the subsequent chapters of this book.

The purpose of this chapter is to look at the nature and kinds of philosophical assumptions that are made in the literature on information systems development and data modeling.

Background

It is a truism to say that computers have become ubiquitous in today's organizations. Since their application in administrative data processing in the mid-1950s, they have become one of the key instruments for improving the formal information processing activities of organizations. In less than four decades, computer-based information systems (IS) have evolved from supporting back office, already formalized, systems such as payroll, to penetrating the entire organization. New applications and technologies have emerged with great fanfare, and the enthusiasm for information systems continues to run high. Indeed, many enthusiasts conceive of information technology as the primary vehicle for organizational problem-solvers, increasing an organization's capacity to cope with external and internal complexity and improve its performance. Nor is there any doubt that information systems will play an even more vital role in tomorrow's organization.

The development of these information systems has received considerable attention in both the popular and academic literature. New methods for designing systems, new approaches for analysis, new strategies for implementing the developed systems, and the like, have proliferated over the past 30 years. Yet, a majority of information systems design approaches conceive of information systems development (ISD) with the assumption that they are technical systems with social consequences. This leads one to focus on IS design problems as problems of technical complexity. Proponents of this view assume that IS development problems can largely be resolved by more sophisticated technical solutions (tools, models, methods and principles).

Introduction

In this chapter, the general philosophical basis laid down in chapter 3 will now be applied to provide a broad but more concrete perspective on systems development. Systems development will be explored in two steps: first, we focus on the underlying concepts; and second, we look at the application of the concepts in various methodologies. More specifically, chapter 4 elaborates on the theoretical concepts of ISD as introduced in chapter 2, and ties them into the paradigmatic notions as discussed in chapter 3. ISD tries to show how the conceptual foundations introduced thus far can actually help us to better understand, organize and analyze the rich variety of approaches which have been proposed in the literature. In chapter 5 we deepen this understanding by analyzing in detail four specific methodologies to ISD.

Our first task in this chapter is to convey a more vivid picture to the reader of how systems development might actually proceed in practice if it were to adhere to different paradigms. To this end we shall provide an idealtype description of the ‘scene’ of systems analysis under the four paradigms identified in chapter 3, thereby illustrating their underlying fundamental concepts in a systems development context. In the last part of this chapter we relate the four paradigms to the evolution of approaches to ISD as introduced in chapter 2.

Paradigms of Information Systems Development

Each of the following four descriptions of systems development was derived from interpreting pools of systems development literature which share the assumptions of a particular paradigm.

Introduction

The purpose of this chapter is to explore in some detail the different schools of data modeling which were introduced in chapter 6. The first school embraces objectivism in data modeling. It follows the footsteps of the empiricalanalytical scientific method. It assumes that reality can be described by independent facts (which corresponds to the empirical base of observational statements in objectivist philosophy). The database captures these facts and data models provide the structure for organizing all the facts into a consistent picture of reality. In accordance with this, objectivist data modeling approaches were called fact-based or fact-oriented in chapter 6. The prominent features of the fact-based school will be discussed in section 7.2.

The second school of data modeling follows the social relativist tradition in the philosophy of science. It assumes that the domain of inquiry is not independent of the observer, and therefore reality cannot be described in terms of independent hard facts. Rather, what counts as reality are socially constructed images which emerge in social interaction, in particular through communication in some language. The details of these images are not completely arbitrary, but depend on the ‘grammar’ (the rules and ‘meanings’) which governs social communication. A data model attempts to formalize some of the informal social rules and meanings into a formalized grammar and hence a data model is a social construction par excellence. In accordance with this insight, subjectivist data modeling approaches were called rule-based in chapter 6.

In these summaries of selected methodologies, it should be noted that in the case of the structured methodologies and prototyping, we are really describing a ‘family of methodologies’ rather than a single approach.

In order to provide a sense of consistency throughout these summaries, the methodology descriptions consist of four parts:

1. (1) an analysis of the reasons why the particular methodology was proposed (its purpose and rationale);

2. (2) a concise examination of the key ideas underlying the methodology by which it hopes to achieve its stated purpose (its focus);

3. (3) a characterization of the methodology's principal stages and their sequence (its phase structure); and

4. (4) a list of its special methods and tools with their intended purpose.

In order to highlight the special features of each methodology, in some cases we relate these features to the classical system life-cycle (cf. the systems analysis textbooks of Kendall and Kendall 1988; Yourdon 1989).

Structured Methodologies

Purpose and rationale

The most common forms of structured methodologies can be traced to the classic works of Gane and Sarson (1979), DeMarco (1978) and Yourdon (1989). They were introduced to cope with the complexity of analysis and design and problems which the complexity caused with descriptions used in the classical life-cycle approach. The latter lacked a clear focus and organization for the analysis and predefined formats for describing and filing the myriad of details that a development exercise collects during the systems development process beginning with vague descriptions of the problem and ending (hopefully) with detailed program specifications and user documentation.

Introduction

This chapter will show that the issues arising in data modeling have close connections to core issues as discussed in the theory of knowledge, epistemology and philosophy of language. The purpose of this chapter is to characterize data modeling in terms of the philosophical debate in these areas and connect it to the four paradigms to the extent as is appropriate. Whilst all of the paradigmatic assumptions have important implications for data modeling, neither the neohumanist nor the radical structuralist paradigm are specifically reflected in the literature on data modeling. Nevertheless, we believe that a neohumanist paradigm could be applied to data modeling. In the following we shall articulate some of its principal implications for data modeling. In addition, while no work has been published on a radical structuralist approach to data modeling (i.e. the equivalent of the UTOPIA project in the process-oriented approaches), we believe that its most important aspect, the articulation of the workers' perspective, could be accomplished within a neohumanist approach.

In order to provide a concrete focus for the philosophical treatment of data modeling in terms of the paradigms, we shall organize the discussion in section 6.3 around the following four questions:

1. (1) The ontological question (what is being modeled?)

2. (2) The epistemological question (why is the result valid?)

3. (3) The social context question (what is the relationship between the social world and data modeling?)

4. (4) […]

Introduction

The purpose of this chapter is two-fold: firstly, the chapter suggests a set of terms and concepts to describe and converse about information systems development which is independent of any particular or preferred way of dealing with it. Not surprisingly, as the IS field evolved, many different and sometimes inconsistent uses of terms to describe key notions appeared. For example, the part of the organization that is targeted for change through an IS development project is variably referred to as utilizing system, domain of change, target system, or universe of discourse. We shall use the term object system to cross-relate these terms coming from different sources. The concepts proposed in this chapter were selected with two requirements in mind:

1. (1) they should be maximally consistent with the literature base; and

2. (2) they should serve as a compass directing us deeper into the underlying philosophical issues often ignored in the literature on ISD.

Secondly, the chapter provides a brief overview of the history of information systems development and data modeling. This analysis serves as a historical background for understanding the origins (genealogy) of theoretical concepts and definitions offered in the chapter. It also provides the historical context for the more detailed treatment of specific systems development methodologies in chapter 5 and the analysis of data modeling approaches in chapter 7.

Introduction

In this book we have tried to provide insights into information systems development and data modeling through a philosophical and conceptual analysis. More specifically, we have sought to meet the two goals articulated in chapter 1:

1. (1) to trace systematically the complexity of IS development to a set of beliefs about its domain of change; and

2. (2) to point out that IS development cannot be reduced to ‘technological fixes’.

The first goal was addressed by demonstrating how a wide range of IS methodologies and data modeling approaches take radically different stances about the nature of the organization, data, information system, and what it means to change them. A careful analysis of the differences led us to perceive the inherent complexity of social change which is associated with IS development. The second goal was addressed by pointing out that there is inherent complexity in the social condition and environment of systems development which escapes technological solutions; indeed, such complexity is often amplified through such technological solutions. We hope that the reader, having taken the time and pains to consider our ideas, agrees with our initial position that the IS community should not ignore the philosophical controversies which have raged over the social sciences during the past decades as they fundamentally impact upon our understanding of IS. These controversies are also reflected in the debate which has arisen about the nature of computer science and information systems as disciplines.

Introduction

This chapter explores, via a paradigmatic assumptions analysis, four theoretically appealing information systems development methodologies (i.e. process-oriented approaches to ISD). Such an analysis is prompted in part by a broadening of the conceptual base in the most recent literature on ISD. At present one can identify several systems development research communities that have coalesced around different paradigmatic beliefs (in the sense of Kuhn 1970) which inform their research efforts. Some researchers have been attracted by the emergence of alternative theoretical foundations and are using them to inspire new ways of thinking about ISD. Examples of such theoretical foundations for ISD are speech act theory, activity theory, critical social theory, self-referential systems theory, semiotics, structuration theory or, with a reactionary turn to the classics, Mao's theory ‘On Contradiction’.

However, many of these new ways of thinking about ISD (some might refer to them as ‘schools’ of ISD) are not driven by an explicit reflection of the philosophical groundings upon which a new theoretical base could be formed. To help understand this issue more clearly, this chapter provides an ex post reconstruction of the philosophical grounding for four influential ‘schools’ of ISD. Our attempt parallels the paradigmatic analysis of contemporary schools of IS by Iivari (1991). However, our goals in selecting these schools were somewhat different.

Selection of Approaches and Plan of Analysis

Whereas Iivari's (1991) purpose was to cover all the major schools of thought in IS development, our initial goal was one of illustrating the influence of the four paradigms in current approaches to ISD.

Though the fields of information system development, in general, and data modeling in particular — the topics of this book — have amassed an impressive amount of research knowledge during the past two decades, they currently lack a global perspective and interpretation. In this context we define information systems development as the application of information technologies (computers and telecommunications) to solve and address problems in managing and coordinating modern organizations. Data modeling is concerned with describing, organizing and analyzing the properties of the ‘rawware’ of information systems — data. A wealth of research in these fields has produced an astonishing array of empirical results and practical insights, conceptual and terminological diversity and confusion, and a large suite of tools and methods. But as many researchers and practioners alike feel, these form an isolated, disjoint, and often contradictory amalgam of knowledge. In such a situation, the synthesis of the existing knowledge is at least as valuable as the addition of more detail in the form of further empirical results, new methods and tools, and refinements in vocabulary, etc. The need for synthesis to decrease the confusion in the area has motivated us to write this book: we seek out the principal, contradictory lines of research in information systems; describe and interpret them and their results in a way which does not deny or hide their differences, but in fact highlights the differences; and thereby hope to make these lines of research understandable.