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The authors explain semi- automatic ontology generation and metadata extraction in depth, along with ontology management and mediation. Further chapters examine how Semantic Web technology is being applied in knowledge management Semantic Information Access and in the next generation of Web services. Semantic Web Technologies: Provides a comprehensive exposition of the state-of-the art in Semantic Web research and key technologies. Explains the use of ontologies and metadata to achieve machine-interpretability.

Book: Semantic Web Technologies : Trends and Research in Ontology-based Systems

Describes methods for ontology learning and metadata generation. Discusses ontology management and evolution, covering ontology change detection and propagation, ontology dependency and mediation. Illustrates the theoretical concepts with three case studies on industrial applications in digital libraries, the legal sector and the telecommunication industry.

Graduate and advanced undergraduate students, academic and industrial researchers in the field will all find Semantic Web Technologies an essential guide to the technologies of the Semantic Web.

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The Semantic Web is not only an area of research, but also a worldwide project where easy-to-construct applications can directly find their communities of users. However, the semantics that are the engines for these applications are still the bottleneck in the development. Therefore one finds a large range of technologies and tricks to populate ontologies with machine understandable meaning of terms in this volume. This varies from the use of top-ontologies via design patterns to extraction of terms from text and alignment of existing terminologies.

In fact, one may see this book not so much as the report of results of research, but rather as a specification of the elements of an emerging methodology for developing legal ontologies. This collection of articles about legal ontologies and Semantic Web applications has its roots in workshops and conferences on Artificial Intelligence AI and Law, most notably, the workshops on ontologies and Semantic Web technology in the legal domain, held in June at Stanford University.

Having easily access to relevant legal information among the rising flood of legal documentation is not only the concern of legal practitioners, but also the life and work of citizens becomes more and more entangled with legal issues. This volume reflects the wisdom, abstracted from experiences accumulated over more than a decade of research and development in this area.

What is an Ontology

It contains a representative overview of the state of the art, covering both theoretical aspects and practical systems. Also national initiatives have played an important role as can be concluded from the overrepresentation of articles from Spain and Italy. As the practical needs for legal information management are certainly not more pressing in these countries than in other countries, we hope that this book will also serve as an argument for further investments in this endeavor. The Semantic Web is not only an area of research, but also a world wide project where easy to construct applications can directly find their communities of users.


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However the semantics that are the engines for these applications are still the bottleneck in the development. Therefore one finds in this volume a large range of technologies and tricks to populate ontologies with machine understandable meaning of terms. Legal knowledge engineering: A modelling approach.

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Information search and retrieval are part of daily routines of the legal profession. Lawyers, judges, prosecutors, and legal clerks usually access a number of electronic resources to browse, search, select, or update legal contents. Legal databases have currently become large digital libraries where the tasks related to information-seeking may sometimes be cumbersome.

Adding semantics to support information search may provide significant results in terms of efficiency, efficacy, and user satisfaction. Semantic technologies may be able to improve legal information search in the judicial and lawyers' domains. However, legal professionals sometimes prefer following routines than changing their information search behavior. New trends in legal ontologies and Semantic Web technologies may help to improve both professional and laymen's skills.


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In this paper we describe a legal core ontology that is part of the Legal Knowledge Interchange Format: a knowledge representation formalism that enables the translation of legal knowledge bases written in different representation formats and formalisms. A legal core ontology can play an important role in the translation of existing legal knowledge bases to other representation formats, in particular as the basis for articulate knowledge serving.

This requires that the ontology has a firm grounding in commonsense and is developed in a principled manner. We describe the theory and methodology underlying the LKIF core ontology, compare it with other ontologies, introduce the concepts it defines, and discuss its use in the formalisation of an EU directive. Ontology design is known to be a difficult task, requiring much more than expertise in an area or competence in logic; legal ontology design, due to the complexity of its domain, makes those difficulties worse. This may be partly due to poor support for requirement analysis in existing tools, but there is also an inherent gap between the purely logical constructs and methods that are expected to be used, and the actual competences and thought habits of legal domain experts.

This paper presents some solutions, based on ontology design patterns, which are intended to make life of legal ontology designers easier. An overview of the typical tasks and services for legal knowledge is presented, the notion of ontology design pattern is introduced, and some excerpts of a reference ontology CLO and its related patterns are included, showing their utility in a simple legal modeling case. The paper reports on the methodology and preliminary results of a case study in automatically extracting ontological knowledge from Italian legislative texts.

We use a fully—implemented ontology learning system T2K that includes a battery of tools for Natural Language Processing NLP , statistical text analysis and machine language learning. Tools are dynamically integrated to provide an incremental representation of the content of vast repositories of unstructured documents. Evaluated results, however preliminary, show the great potential of NLP—powered incremental systems like T2K for accurate large—scale semi—automatic extraction of legal ontologies.

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This paper deals with the use of computational linguistic analysis techniques for information access and ontology learning within the legal domain. We present a rule-based approach for extracting and analysing definitions from parsed text and evaluate it on a corpus of about German court decisions. The results are applied to improve the quality of a text based ontology learning method on this corpus. The automatic detection of arguments in text regards a relatively new area at the intersection of Natural Language Processing, Information Retrieval and Legal Information Systems.

This paper presents some fundamental issues when processing texts that contain argumentation. Furthermore, our research bridges different areas, including the legal field and the Semantic Web, where argumentation detection and reconstruction could be beneficial.

Semantic Web Technologies : Trends and Research in Ontology-based Systems

Finally, it analyses several methodologies to accomplish this task, providing results from different experiments done over several kinds of texts, specially legal reports. Law information retrieval systems use law ontologies to represent semantic objects, to associate them with law documents and to make inferences about them.

A number of law ontologies have been proposed in the literature, what shows the variety of approaches pointing to the need of matching systems. We present a proposal based on argumentation to match law ontologies, as an approach to be considered for this problem. Argumentation is used to combine different techniques for ontology matching. Such approaches are encapsulated by agents that apply individual matching algorithms and cooperate in order to exchange their local results arguments.

Next, based on their preferences and confidence, the agents compute their preferred matching sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. In order to extract the full potential from Internet-wide content sharing and reuse, the underlying copyright issues must be taken into account. The novel requirements are not satisfied by traditional Digital Rights Management.

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Open licensing initiatives seem more appropriate, but they lack the required computerised support. Our proposal facilitates interoperation while providing a rich framework that accommodates copyright law and copes with custom licensing schemes. The ontology provides the building blocks for flexible machine-understandable licenses and facilitates implementation because DL reasoners can be directly used for license checking.