The basic principle of decision making based on substantive rationality is very simple: one seeks to maximize expected utility. This principle has led to a body of mathematics that accommodates ways to rank-order expectations and to search or to solve for the option (or options) that meet the optimality criteria. The major mathematical components of this approach are utility theory, probability theory, and calculus.

The basic principle of decision making based on intrinsic rationality is also very simple: one seeks acceptable tradeoffs. To be useful, this principle must be supported by a body of mathematics that accommodates ways to formulate tradeoffs and to identify the options that meet the satisficing criteria. This chapter introduces such a mathematical structure. It also is composed of utility theory, probability theory, and calculus, but with some important differences in the structure and the application of these components (Stirling and Morrell, 1991; Stirling, 1993; Stirling, 1994; Stirling et al., 1996a; Stirling et al., 1996c; Stirling et al., 1996b; Goodrich et al., 1999; Stirling and Goodrich, 1999a; Goodrich et al., 2000).

That decision makers can rarely be certain is obvious. The question is, what are they uncertain about? The most well-studied notion of uncertainty is epistemic uncertainty, or uncertainty that arises due to insufficient knowledge. Such uncertainty is usually attributed to randomness or imprecision. The effect of epistemic uncertainty is to increase the likelihood of making erroneous decisions. The worst thing one can do in the presence of epistemic uncertainty is to ignore it. It is far better to devise models that account for as much of the uncertainty as can be described. Consequently, a large body of theories of decision making in the presence of less than complete information has been developed over many decades. I do not propose to give an exhaustive treatment of the way epistemic uncertainty is accounted for under classical decision-making paradigms, but instead summarize two ways to deal with uncertainty. The first is the classical Bayesian approach of calculating expected utility, and the second is the use of convex sets of utility functions.

Probability theory developed as a means of analyzing the notion of chance and, as a mathematical discipline, it has developed in a rigorous manner based on a system of precise definitions and axioms. However, the syntax of probability theory exists independently of its use as a means of expressing and manipulating information and of quantifying the semantic notions of belief and likelihood regarding natural entities. In this book we employ the syntax of probability theory to quantify semantic notions that relate to the synthesis of artificial entities. In this appendix we present the basic notions of probability theory. However, since much of the terminology is motivated by the historical semantics, it will be necessary to supplement the standard treatment with terminology to render the definitions more relevant to our usage.

We begin by establishing the notation that is used in this book.

Definition C.1

A set is a collection of simple entities, called elements. If A is a set and the points ω1, ω2, … are its elements, we denote this relationship by the notation

A = {ω1, ω2, …}.

If ω is an element of the set A, we denote this relationship by the notation ω ∈ A, where ∈ is the element inclusion symbol.

Often, we will specify a set by the properties of the elements. Suppose A comprises the set of all points ω such that ω ∈ S possesses property P.

This chapter has two main parts. The first part examines the application of existing international copyright agreements to the protection of databases. In the course of that examination, the argument is made that the Member States of the EU may be in breach of their international copyright obligations to accord national treatment and most favoured nation status to other members of relevant international agreements, by not providing the same sui generis protection for foreign databases as that provided to EU databases. This argument is based on the points made in Chapter 3 concerning the overlap between the sui generis right and copyright. The Directive's sui generis protection may be categorised as copyright and, consequently, national treatment must be accorded to all databases, regardless of their geographical origin. In turn, this has implications for the argument that other countries, such as the United States, should provide similar protection in order to obtain reciprocal protection from the EU. If the EU is already obliged to accord national treatment, that argument loses all merit.

The second part of the chapter examines the steps taken to date towards a multilateral treaty that would deal specifically with database protection. It also discusses the myriad of bilateral agreements entered into by the EU with other countries that effectively ‘export’ the sui generis right of the Directive to those countries as part of the acquis communitaire of the EU. The very nature of the discussion concerning databases requires some consideration of these international legal dimensions.

We live in the Age of Information. Information is money. So is time. The economies of the First World are dominated by the creation, manipulation and use of information and the time it takes to do so. These economies do not suffer from a shortage of information; they suffer from the difficulties associated with collecting, organising, accessing, maintaining and presenting it. Databases are designed to help deal with these difficulties. They are collections of information arranged in such a way that one or more items of information within them may be retrieved by any person with access to the collection containing those items. Therefore, databases are big business because they contain important and copious amounts of information and they reduce the time taken to access that information. And where there is big business, the law and lawyers inevitably follow.

But information is more than money and databases are more than big business. Information and databases are critical to science, the legal system itself, education and all those aspects of life that are improved by them. Consequently, there are important issues of social and political policy to be considered in the regulation of access to, and use of, databases. Again, where there are such critical issues at stake, the law has a role to play.

There is an inevitable tension between the commercial and the socio-political role of databases that leads to complexities in developing an appropriate model for their legal protection.

This chapter examines the transposition of the Directive into the domestic laws of the EU Member States. It does so by focusing on the protection of databases in nine of the Member States: Belgium, France, Germany, Ireland, Italy, the Netherlands, Spain, Sweden and the UK. The section below describes the legislation and case law of those countries relating to copyright and unfair competition as they relate to databases and the sui generis right. In order to avoid repetition, only particular features of the transposing legislation that are of note are discussed.

These nine countries were chosen for a number of reasons. First, they represent a broad range of pre- and post-Directive approaches to protection of databases. For example, Ireland and the UK had sweat of the brow copyright protection for databases prior to transposing the Directive. Most other countries did not have such copyright laws but had other schemes in place that conferred at least some protection on the non-original aspects of databases. For example, Sweden had its catalogue laws that influenced the Directive. Germany and other countries had, and still have, unfair competition laws that prevent parasitic copying by a competitor. Second, these nine countries represent the vast majority of the population of the EU and, finally, the vast majority of EU investment in databases and publishing occurs in those countries.

After examining the nine individual countries, the main issues raised by the transposing legislation and related case law are summarised. The chapter begins with three tables.

Mark Davison's book on database protection covers a vital aspect of the digital revolution. Indeed, the whole issue cries out for a place in this series. Databases stand at the juncture between information as such and the expression of literary and artistic ideas. From the first perspective, information appears to be a necessary element in social existence and so arguably it should be freely accessible to all. From the second, the need to provide an incentive for the costly business of assembling large databases argues for an equivalent appropriation to that given to creators and their producers by copyright. Deciding how to structure this crossroads – be it with filter lanes or with stop signs – calls for refined legal engineering. What has been done so far to regulate this space has in considerable degree depended on attitudes towards traffic which were formed in a horsedrawn era. Now, motorised vehicles bearing enormous loads of information bear down and have somehow to be accommodated. Hard-pressed legislators and courts have done what struck them as best, but it is far too early to say whether anything like a reasonable balance has been reached between free flow and controlled access.

It will be some time before we can see whether by and large we are offering stimulants to investment in data accumulation which are what is needed, but not evidently more than that. Mark Davison draws on the experience to date in the United States, the British Commonwealth and the European Union.

There are three basic models for legal protection of databases that can be easily identified.

1. Copyright protection is provided at a low level of originality. Under this model, copyright protection is provided for compilations on the basis that a substantial investment has been made in the compilation. This model presently applies in a number of common law countries such as Australia. The effect is that a database user cannot take a substantial amount of the data contained within the database.

2. Copyright protection is provided if there is some creativity in the selection or arrangement of the database material, coupled with a sui generis right. Copyright prevents the taking of the selection or arrangement. The sui generis right protects the investment in obtaining, verifying and presenting the data within the database. It does so by prohibiting the unauthorised extraction or re-utilisation of a substantial part of the data, conferring exclusive property rights in the data as it exists in the database upon the owner of the database. The Directive contains this model.

3. Copyright protection is provided for the creativity in the selection or arrangement of the database material. No protection is provided for the data contained within the database. At the time of writing, this model operates in the United States. Various bills have been placed before Congress to provide additional protection, but none has been passed as yet. The latest bills have proposed protection for the contents of databases where the database owner can demonstrate that a defendant's actions have materially harmed its primary or related market for the database.