Conventional IVF insemination has been providing satisfactory results in most cases in absence of male-factor infertility. However, low fertilization or complete fertilization failure can happen not only when sperm parameters are impaired but occasionally also when there is no detected male factor. In these occasions, to rescue the IVF treatment cycle, ICSI re-insemination of the failed-fertilized oocytes (after the original conventional insemination) may be attempted. Oocyte aging plays an important role, as because fertilization check is usually performed 16–18 hours after conventional insemination, when failure of fertilization can be detected, however, by that time outcomes after rescue ICSI is mostly suboptimal, if attempted. Alternatively, conventionally inseminated oocytes can be examined much sooner to detect signs of fertilization. It has been demonstrated, if oocytes are submitted to rescue ICSI within 4–8 hours after the initial insemination, then laboratory and clinical outcomes are significantly improved. Since conventional IVF insemination remains to be used frequently around the world, adequately performed rescue ICSI is a viable option to save IVF treatment cycles when unexpected low or total fertilization failure occur.

In this chapter we present a variant of the tableau algorithm that can accommodate the SHIQ language. We first summarise the elements of the tableau reasoning that have been introduced so far. Next, we discuss the techniques to support each new construct of the SHIQ language: transitivity, role hierarchy, inverse roles, functional restrictions and qualified number restrictions. Finally we describe the full SHIQ tableau algorithm, first only for TBox inference and then for reasoning over ABoxes and TBoxes together. The chapter is concluded with a discussion of optimisation techniques for the SHIQ tableau algorithm.

The discussion follows the papers [63, 60], although parts of the formalism have been simplified. Detailed proofs of the properties of the algorithm can also be found there.

An outline of the SHIQ tableau algorithm

First we reiterate the main characteristics of the ALCN tableau algorithm with respect to a possibly non-empty TBox (see Section 5.4). The purpose of this discussion is to highlight the most important features that will be reused in the SHIQ algorithm.

1. (1) The goal of the tableau algorithm is to decide whether a root concept C0 is satisfiable w.r.t. a (possibly empty) TBox T. To make the following discussion simpler, we will often omit the reference to the TBox.

2. (2) […]

The aim of this chapter is to introduce some major problems associated with the World Wide Web that have led to the development of its new generation, the Semantic Web.

The chapter has two main parts. In the first we describe the structure of the Internet, the different kinds of web pages (static and dynamic) and their role in the process of information storage. Here we also introduce the concept of web forms and Common Gateway Interface (CGI) technology and its more advanced alternatives.

In the second part of the chapter we examine how traditional search engines work, what their limits are and how they fare with heterogeneous information sources. We illustrate the problems associated with searching the Web and briefly describe possible solutions. One of these is the Semantic Web approach, which is described in more detail in later chapters.

For readers familiar with the Internet we suggest skipping the first section and starting at Section 1.2.

The architecture of the web

The World Wide Web is made up of servers and clients. Servers store different kinds of information in various ways. Most often these pieces of information are stored in the form of web pages (also called homepages), which are essentially standard text files with a special structure.

In this chapter we focus on heavyweight ontologies and on the role they play in the Semantic Web. We introduce the Web Ontology Language OWL, which is based on Description Logic and which was created as an extension of the RDF schema language (discussed in Section 2.6).

In Section 8.1 we give an introductory overview of the OWL language. Next, in Section 8.2, we present the details of the first OWL standard. Finally, in Section 8.3, we discuss the recently released extension of OWL, the OWL 2 standard.

Unless stated otherwise, we will use the term “OWL” when discussing the features present in both the initial and the recent standards. The terms “OWL 1” and “OWL 2” are used to refer to the first and the recent variant of the Web Ontology Language, respectively.

The language OWL – an introduction

The deficiencies of RDF schema and increasing demand led to the development of a large number of ontology languages. At the end of the last millennium, the two most significant languages were the OIL (Ontology Interface Layer) [37] and the DAML-ONT (DARPA Agent Markup Language) [52] languages. The former was developed by the University of Manchester, the latter by the United States Department of Defense (DoD). Both languages were designed with Description Logic in mind; OIL, in particular, is suited for the FaCT reasoner [55] and hence it realises the SHIQ language class.

The present chapter introduces the Semantic Web and its philosophy. This involves two main ideas. The first is to associate meta-information with Internet-based resources. The second is to reason about this type of information. We show how these two ideas can help in solving the problems mentioned in the previous chapter.

Having introduced the main concepts we continue the chapter by describing technologies that can be used for representing meta-information in a uniform way. First we introduce the XML language, which forms the basis of the Semantic Web as a standard information exchange format. Then we describe the RDF language; this has an XML notation as well as other representations and can be used to associate meta-information to an arbitrary resource. By doing this we can extend web contents with computer-processable semantics.

Subsequently, we introduce the RDF schema language, which provides the background knowledge that is essential to do reasoning on meta-information. We discuss the similarities and differences between RDF schemas and traditional object-oriented modelling paradigms.

We conclude the chapter by presenting several applications that directly or indirectly use RDF descriptions during their operation.

Introduction

The Semantic Web approach was originated by Tim Berners-Lee, the father of the World Wide Web and related technologies (URI, HTTP, HTML etc.). The approach is based on two fundamental ideas.