A semiotics of Stamper (1973), based on the work of Peirce (1931–58), Morris (1938, 1946) and on others, and on ‘information theory’ (Shannon & Weaver 1949), has evolved into a set of semiotic methods for information systems. A radical, subjectivist stance has been accepted as the basic philosophy for developing the set of methods and tools for information systems development. In this chapter, the discussion will focus on the examination of the subjectivist paradigm and the semiotic framework (Stamper et al. 1988).

Philosophical stance

A paradigm is a set of the most fundamental assumptions adopted by a professional community that allows its members to share similar perceptions and engage in commonly shared practices. Scientific achievements recognised in the particular community and research traditions educate its members to commit themselves to the same rules and standards for scientific practice (Kuhn 1962). Adoption of a certain paradigm will determine the way of exploring the world; it will determine the research theory and method. The usual considerations on scientific paradigms may be complemented by considering a set of presuppositions as paradigmatic, thus relating the discussion to philosophy.

Objectivist paradigm

A predominant philosophical position is the objectivist paradigm which assumes that there is a subject-independent world, some objective reality. Objectivism in its rigorous forms regards the universe as being made up of self-existent entities.

If the objective of a system analysis is to understand and specify the users' requirements, then the next objective is to produce a design of a computer information system. The core of a computer information system comprises a database and other application programs. This chapter will address the semantic aspect of the computer information systems, and discuss the relationship between semantic models and database design.

The semantic aspect of databases

Data and code in a database are meaningless until someone assigns a meaning to them and someone is able to interpret them. The meaning of data is rooted in social and cultural conventions and norms. The assignment of meaning to the data and interpretation of the data have to follow the same social and cultural norms. The interpretation is a complex, creative act that relies on personal knowledge and understanding of the norms. A successful use of data and derivation of information meaningful to a user is a key issue in databases. This issue cannot be resolved by technical means alone but requires social and organisational arrangements.

There can be two kinds of meanings distinguished: intension (sense) and extension (or reference). These two notions can be applied to predicates, propositions and sentences. The intension of a predicate, i.e. its sense, is identified with the property it expresses; its extension is the generalised class of referents in the world of affairs that possess the property. The intension of a proposition is determined by the meanings of the predicates used; the extension is its correspondence to the world of affairs.

The method of Semantic Analysis offers a means of representing information requirements and database modelling. Based on the database theory and semiotic methods, a semantic temporal database is proposed. The semantic temporal database provides a technology of management of the data with semantic and temporal properties. A semantic temporal database language, LEGOL, has been developed for the specification of norms. LEGOL statements can specify constraints and triggers, and can be executed by a LEGOL interpreter.

Databases

A database, from the information technology point of view, can be regarded as a kind of electronic filing cabinet (Date 1995, p. 2). It can be defined as a persistent collection of logically related data that allows shared access by many users. A DBMS (Data Base Management System) is the application-independent software that protects and manages databases. Since the late 1960s when the pioneering DBMS, IMS, was published, the database technology has provided ever improving tools for information management. Since then, the development of new types of DBMS and research into new ways of organising information have been taking place. This section provides a quick review of some major contemporary types of database systems and of the presentation of the semantic temporal databases which are considered highly relevant to business information management purposes.

Developments in databases management systems

Relational DBMS is the most widespread and popularly used type of database systems nowadays. Other types of systems are also being introduced to meet diversified application purposes, typically the objected-oriented databases and deductive databases.

A sign has a meaning, and it can be used intentionally for communication. Pragmatics, as a branch of semiotics, is concerned with the relationships between an intentional use of a sign and the resulting behaviour of responsible agents in a social context. Communication takes place successfully when a meaningful sign is used with an appropriate intention between the two parties involved (e.g. speaker and listener).

This chapter addresses the effects of using signs in organisations. Before introducing the semiotic approach, various approaches to and techniques for analysis of the pragmatic aspect of signs are discussed in the chapter, such as speech act theory, functional grammar, and deontic logic. The semiotic approach distinguishes a number of elements in a communication act: propositions, propositional (or illocutionary) attitudes and perlocutionary effects. A communication act will further result in a variety of commitments and responsibilities. The method of Norm Analysis introduced in this chapter provides a formalism for one to identify and specify these important notions in analysing and modelling social and organisational aspects of communications.

Human communication

A social community is a purposeful system in which human beings act and interact with each other for achieving goals that may relate to the community or its individuals. ‘Doing things with words’ in a concerted way becomes a necessity for fulfilling ever more complex objectives of social beings in ever more complex organisations. Communication is the indispensable means by which agents in society coordinate their actions to achieve their goals.

Information analysis is also called information requirements analysis, or requirements studies. It shares with knowledge representation many fundamental concepts and principles. Similarities are found in techniques and methods for both. They both address how people understand the world and how to represent their understanding. Meaning of symbols and languages used in modelling is a central issue for both.

‘All men by nature desire to know’ – said Aristotle in his book Metaphysics. As an agent experiences in the flux of the world in which he acts, his faculty of sensation enables him to feel and observe affairs around him. His memory helps him to accumulate the observations and from them he learns about the world and knows what he can act upon in given circumstances. Many philosophers and scientists, such as psychologists and linguists, have been preoccupied with the study of knowledge. As computer scientists have joined in the inquiry, new perspectives of the study have been suddenly broadened. Knowledge representation has become one of the most important areas of study, because it is directly related to the exploitation of human knowledge by means of artificial intelligence, (deductive) databases, and other computer-supported methods. Each theory of knowledge (epistemology) presupposes a semantic theory; otherwise knowledge cannot be captured and represented with any language or sign system. Knowledge representation is about meanings, which are relationships between signs and the other things that they stand for.

Infomation and information systems

What is information? Many people have attempted to give a definition but most of them are not complete. A typical explanation is that information is processed data that has meanings to its users. But then questions arise in what meaning is. If information is to the study of information as object is to physics, and there are many laws by which we can study objects, then what are the laws by which we can study information? What is the study of information anyway?

What can be said here is that information is not a simple, primitive notion. Devlin (1991) compares the difficulties for a man in the Iron Age to answer the question ‘What is iron?’ and for a man in today's Information Age the question ‘What is information?’ To point to various artefacts of iron in order to answer his question would not be satisfactory; to demonstrate some properties of information as an answer to ‘What is information?’ is not good enough either. People can feel the possession of information, and can create and can use information. They gather it, store it, process it, transmit it, use it, sell it and buy it. It seems our lives depend on it; yet no one can tell what exactly it is.

In order to understand the nature of information, one may have to find some fundamental and primitive notions with which the question can be investigated and explained.

Development of a computerised system normally goes through several stages, and this whole process is termed a system development ‘lifecycle’. There are various lifecycle definitions (see Leslie (1986), Macro & Buxton (1987), Olle et al. (1991) for example). Many researchers have been engaged in bettering methods for each of the phases in a lifecycle. Some of the methods are aimed at one of the phases while others are claimed to be useful for more than one of them. Recently, a great deal of attention has been paid to user requirement analysis and specification. This is because, on examining the sources of difficulty for large systems projects, we find that the incorrect code is a relatively insignificant factor, dwarfed by incorrect functional specification and (even more significantly) incorrect requirements (Boehm 1981; Goguen 1992).

There are many ways to phase activities in systems development. Macro & Buxton (1987) point out that many models may be excessively simple while others are extremely elaborate. In general, activities of systems development can be grouped under a few headings: conceptualisation of systems scope, requirement analysis, systems design, implementation, validation, acceptance, maintenance, and, finally, obsolescence (which may be followed by activities of developing a new version of the system). The research programme MEASUR (Stamper 1993) has developed a set of methods to deal with all aspects of information systems development.

This appendix, as a supplement to section 10.2, supplies further details of Semantic Templates (ST) and the use of ST for database design.

Definition of ST

The definition of ST, basically following a syntax of Backus–Naur form, describes the structure of a semantic template.

ST:=‘<’ agent,ST,mood+,mood–,time+, time– ‘>’| ST:= ‘<’ agent, action, time+,time–‘>’;

agent:= agent performing the action;

action:= realisation of affordance;

mood+:= mood;

mood–:= mood;

mood:= proposal | inducement | forecast | wish | palinode | contrition | assertion | valuation;

proposal:= ‘request’|‘ask’|‘beg’|‘command’|‘insist’|‘suggest’|‘promise’|‘guarantee’;

inducement:= ‘reward’|‘threaten’|‘warn’|‘tempt’;

forecast:= ‘predict’|‘assume’|‘plan’|‘accept’;

wish:= ‘want’|‘hope’|‘expect’|‘desire’;

palinode:= ‘retract’|‘annul’|‘revoke’|‘deny’;

contrition:= ‘regret’|‘apologise’;

assertion:= ‘assert’|‘claim’|‘report’|‘notify’|‘affirm’|‘assure’|‘argue’|‘declare’;

valuation:= ‘judge’|‘appraise’|‘blame’|‘criticise’|‘accuse’|‘object’;

time+:= time;

time–:= time;

time:= absolute time or relative time (by reference to another action).

The right-hand phrases in italics are explanations of the possible value types of the left-hand items. For example, the ‘agent’ is defined as ‘agent performing the action’, which refers to the agent appearing on the ontology chart and relating to the action as the antecedent. The ‘action’ is defined as ‘realisation of affordance’; the affordance should also be predefined on the ontology chart so that there can be a realised instance of the affordance. This can be illustrated by relating to the example shown in Figure 9.4, and it will be used throughout this appendix. In that figure, a person, John, is the agent; a particular case of John's being absent is a realisation of the affordance ‘absence’.

Normbase is not just a software system. It represents a new way of managing information. It also represents a new approach to the development of information systems using semiotic methods. The chapter will introduce the concept of Normbase, and the Normbase system as a software environment for managing information. It will also discuss how the Normbase system can be used for supporting business management and decision-making.

The Normbases concept

Norms are parts of business knowledge that determine the meanings of the data in databases. The knowledge serves as a constraint upon the organisation and utilisation of the data. In order to allow only meaningful interpretations of and operations on the data, the knowledge must be consolidated into the technical information systems in a proper way.

The database discipline has established an approach to incorporating business knowledge into the technical information systems following the principle of data independence. Data independence, as one of the objects of database systems, provides an important separation between data and applications. It furnishes an immunity of application programs from changes of the data storage structure and access strategy (Date 1995). Data independence is achieved by isolating the domain-specific (knowledge) parts of the database system from the general (supporting) part. This process of knowledge abstraction can be applied not only to databases, but also to programming techniques. In object-oriented programming languages, the technique of abstract data types allows one to specify certain operations on a data type without having to affect the internal representation of the instances.

The word ‘semiotics’ comes from the Greek for ‘symptom’. Charles Sanders Peirce (1839–1914), who was primarily a logician and competent in mathematics and many other branches of science, including astronomy, chemistry, physics, geology and meteorology, founded semiotics as the ‘formal doctrine of signs’. At almost the same time, Ferdinand de Saussure (1857–1913) founded semiology, a European school of semiotics. Semiology aims at discovering ‘what constitutes signs and what laws govern them’ (a quote of Saussure, cited in Hawkes (1977, p. 123)), with a slight emphasis on social psychology and general psychology. Semiotics covers the whole cycle of a sign from its creation, through its processing, to its use, with more emphasis on the effect of signs. Although, in the literature, sometimes no clear distinction is made between semiotics and semiology, it is the former which will be the theme of study in this book.

There are three distinct fields of semiotics: syntactics (or syntax), semantics and pragmatics, which go back ultimately to Peirce (cf. Lyons (1977)). Morris (1938) made semiotics more generally familiar as a science of signs, to which he made many important contributions, largely from a behavioural standpoint. According to Morris, pragmatics deals with the origin, uses and effects of signs within the behaviour in which they occur. Semantics deals with the signification of signs in all modes of signifying; syntax deals with the combination of signs without regard to their specific signification or their relation to the behaviour in which they occur.

A business system is a real information system, which is infinitely rich and complex. One can never exhaustively study a social or business organisation. What is modelled is always a part of it; and what is seen is just a realisation (or an instance) of a pattern of behaviour of some agent. If one wishes to model a business system one has to focus on the level of pattern of behaviour. The method of Semantic Analysis provides a means for these purposes by devising a canonical formalism with focus on the responsible agent and his repertoire of behaviour. This method covers a range of activities in information modelling such as requirements elicitation, analysis, specification and representation.

Theoretical aspects of Semantic Analysis

The relationship between behaviour and knowledge is in two directions. In one direction, an agent learns about the world through his actions to gain knowledge so that he gets to know exactly the meanings and boundaries of objects, concepts and relations. On the other side, the behaviour manifests knowledge that the agent possesses. The functions of both sides work at the same time, i.e., what he knows tells him what to do; what he does reflects what he knows (partially, because what he does may be a kind of trail to learn some new knowledge). Any rational action of the agent is constrained by the repertoire of behaviour and directed by his knowledge of the world. This repertoire of behaviour can be seen as affordances.

Information systems are a multi-disciplinary subject, whose objects of study are information and its functions, information technology and its use in organisational contexts. For nearly three decades, scholars and practitioners have been pursuing effective paradigms, approaches, methods and techniques for developing and engineering information systems. The book is intended to contribute to this direction.

The research work on which the book is based began in 1989 in Twente University, the Netherlands, where I joined a team led by Professor Ronald Stamper. The team has been preoccupied by a series of philosophical and methodological investigations into information systems for a long time. My work at that time, with a focus on information modelling, was just a part of the large programme entitled MEASUR.

The research programme began in 1973, marked by Stamper's book on information. It was first called LEGOL, which aimed to deliver a set of legally oriented techniques for requirements specification. It soon extended into a research effort into Methods for Eliciting, Analysing and Specifying Users' Requirements (hence MEASUR). In the last ten years, the programme has further expanded into a set of methods to deal with all aspects of information systems. The theory of organisational semiotics is a key foundation for the methods and techniques developed within MEASUR. These methods and techniques enable one to understand and articulate the business problem and its context under the study, to capture semantics and intentions of users in requirement models, and also to implement technical information systems that are flexible and adaptable to the organisational change.

The CRIS case was invented by IFIP (the International Federation for Information Processing) for the comparative review of information systems design methodologies. The case definition can be found in Information Systems Design Methodologies (Olle et al. 1982).

In this appendix, the CRIS case is studied using the method of Semantic Analysis which results in an ontology chart (Figure B.1). In order to test LEGOL language and the interpreter, questions are made and then translated into LEGOL expressions. The LEGOL statements were executed by the LEGOL interpreter, a part of an early prototype of the Normbase run on a VAX station, and the results were produced based on some imaginary data stored in the Normbase. Section B.1 contains some questions and the LEGOL statements, and section B.2 presents the corresponding output from the Normbase version.

Questions and LEGOL statements

In this section, there are questions concerning the CRIS case, and statements in LEGOL that will produce the answers, printed below each question.

(1) What are the Technical Committees of the various learned societies on our records?

TC

(2) Who are the current member organizations of IFIP?

current membership (national-org, IFIP)

(3) What Working Groups now exist?

WG

or

WG (TC)

(4) When was WG8.1 started?

start-of WG# “WG8.1”

(5) Which are the newly created Working Groups after 1980?

start-of WG after @1980

or

start-of WG after start-of WG# “WG8.1”

(Note: the ‘at sign’ (i.e. @) is an ad hoc solution for making that version of the compiler distinguish what after the ‘at sign’ will be a number for ‘year’.)

In this chapter, the application of Semantic Analysis, Norm Analysis and the Normbase system in the development of a land resource information system offers an example of adopting the semiotic approach to cover activities of all stages of information systems development.

Background

The assignment was originally for students in a postgraduate GIS (geographic information systems) course at the International Institute for Aerospace Survey and Earth Science, the Netherlands. The course participants, after having worked in different disciplinary fields for many years, came from all over the world. They were supposed to use some structured method to carry out the systems analysis and design. The purpose of applying the semiotic methods was originally for a simple comparison between different approaches. However, for the purposes of this chapter, the analysis and design with the other approach will not be presented.

The objective of the case is to develop an information system for management of land resources, for an imaginary country, Snake Island. This project represents a typical type of information systems that are currently in high demand in many countries, especially the developing countries. Developing such a system requires tremendous effort, because very often such a system involves a heavy investment on expressive GIS hardware and software, and a costly multidisciplinary team of experts. On the other hand, such a system normally has a significant political, economic or other impact on the region that the system is supposed to serve.