A Comparison of Four Ontologies for the Design of Legal Knowledge Systems

There is a growing interest in how people conceptualise the legal domain for the purpose of legal knowledge systems. In this paper we discuss four such conceptualisations (referred to as ontologies): McCarty's language for legal discourse, Stamper's norma formalism, Valente's functional ontology of law, and the ontology of Van Kralingen and Visser. We present criteria for a comparison of the ontologies and discuss the strengths and weaknesses of the ontologies in relation to these criteria. Moreover, we critically review the criteria.     

A principled approach to developing legal knowledge systems

In this article we present a principled, four-phased approach to the development of legal knowledge systems. We set out from the well-studied CommonKADS method for the development of knowledge systems and tailor this method to the legal domain. In particular, we propose a generic legal ontology, and describe the creation of statute-specific ontologies to adopt the method for building legal systems. In the construction of these ontologies, we start from a theoretical analysis of the legal domain. The well-known example of the Imperial College Library Regulations (ICLR) is used to illustrate the method.     

Legal Ontologies in Knowledge Engineering and Information Management

In this article we describe two core ontologies of law that specify knowledge that is common to all domains of law. The first one, FOLaw describes and explains dependencies between types of knowledge in legal reasoning; the second one, LRI-Core ontology, captures the main concepts in legal information processing. Although FOLaw has shown to be of high practical value in various applied European ICT projects, its reuse is rather limited as it is rather concerned with the structure of legal reasoning than with legal knowledge itself: as many other “legal core ontologies”, FOLaw is therefore rather an epistemological framework than an ontology. Therefore, we also developed LRI-Core. As we argue here that legal knowledge is based to a large extend on common-sense knowledge, LRI-Core is particularly inspired by research on abstract common-sense concepts. The main categories of LRI-Core are: physical, mental and abstract concepts. Roles cover in particular social worlds. Another special category are occurrences; terms that denote events and situations. We illustrate the use of LRI-Core with an ontology for Dutch criminal law, developed in the e-Court European project.     

基于本体论的应急系统知识表示的研究

论文在对知识表示及国内外有关本体库研究的基础上,提出将知识表示方法中的框架与谓词逻辑相结合,作为本体知识的一种描述方法,去定义国防动员应急决策支持系统中通信内容的共享本体,给出基于OWL+RDF+XML的形式化描述。并利用本体对知识进行领域分类,同时对决策者的查询信息进行规范。     

Ontologies: How can They be Built?

Ontologies are an important component in many areas, such as knowledge management and organization, electronic commerce and information retrieval and extraction. Several methodologies for ontology building have been proposed. In this article, we provide an overview of ontology building. We start by characterizing the ontology building process and its life cycle. We present the most representative methodologies for building ontologies from scratch, and the proposed techniques, guidelines and methods to help in the construction task. We analyze and compare these methodologies. We describe current research issues in ontology reuse. Finally, we discuss the current trends in ontology building and its future challenges, namely, the new issues for building ontologies for the Semantic Web.     

DOLCE ergo SUMO: On foundational and domain models in the SmartWeb Integrated Ontology (SWIntO)

Increased availability of mobile computing, such as personal digital assistants (PDAs), creates the potential for constant and intelligent access to up-to-date, integrated and detailed information from the Web, regardless of one's actual geographical position. Intelligent question-answering requires the representation of knowledge from various domains, such as the navigational and discourse context of the user, potential user questions, the information provided by Web services and so on, for example in the form of ontologies. Within the context of the SmartWeb project, we have developed a number of domain-specific ontologies that are relevant for mobile and intelligent user interfaces to open-domain question-answering and information services on the Web. To integrate the various domain-specific ontologies, we have developed a foundational ontology, the SmartSUMO ontology, on the basis of the DOLCE and SUMO ontologies. This allows us to combine all the developed ontologies into a single SmartWeb Integrated Ontology (SWIntO) having a common modeling basis with conceptual clarity and the provision of ontology design patterns for modeling consistency. In this paper, we present SWIntO, describe the design choices we made in its construction, illustrate the use of the ontology through a number of applications, and discuss some of the lessons learned from our experiences.     

A methodology for constructing of philosophy ontology based on philosophical texts

An ontology is a crucial factor for the success of the Semantic Web and other knowledge-based systems in terms of share and reuse of domain knowledge. However, there are a few concrete ontologies within actual knowledge domains including learning domains. In this paper, we develop an ontology which is an explicit formal specification of concepts and semantic relations among them in philosophy. We call it a philosophy ontology. Our philosophy is a formal specification of philosophical knowledge including knowledge of contents of classical texts of philosophy. We propose a methodology, which consists of detailed guidelines and templates, for constructing text-based ontology. Our methodology consists of 3 major steps and 14 minor steps. To implement the philosophy ontology, we develop an ontology management system based on Topic Maps. Our system includes a semi-automatic translator for creating Topic Map documents from the output of conceptualization steps and other tools to construct, store, retrieve ontologies based on Topic Maps. Our methodology and tools can be applied to other learning domain ontologies, such as history, literature, arts, and music.     

A knowledge encapsulation approach to ontology modularization

The development of monolithic ontologies for complex domains may face various challenges in reasoning and implementation. The notion of modularity can be employed for developing more efficient ontologies, especially in distributed environments. In this paper, we introduce a framework for developing ontologies in a modular manner. We describe the interface-based modular ontology formalism, (IBF), which theoretically supports the framework. The main feature of the framework is its support for knowledge encapsulation, i.e., it allows ontologies to define their main content using well-defined interfaces, such that their knowledge bases can only be accessed by other ontologies through these interfaces. An important implication of the proposed framework is that ontology modules can be developed completely independent of each other’s signature and languages. Such modules are free to only utilize the required knowledge segments of the others. We also investigate the issues of inconsistency in the proposed modular ontology framework. We provide solutions for isolating inconsistent ontology modules from the other parts of a modular ontology and also resolve inconsistencies which may be arisen by integrating consistent knowledge bases.     

Onyx: A new Canvas-based tool for visualizing biomedical and health ontologies

Ontologies provide formal, machine-readable, and human-interpretable representations of domain knowledge. Therefore, ontologies have come into question with the development of Semantic Web technologies. People who want to use ontologies need an understanding of the ontology, but this understanding is very difficult to attain if the ontology user lacks the background knowledge necessary to comprehend the ontology or if the ontology is very large. Thus, software tools that facilitate the understanding of ontologies are needed. Ontology visualization is an important research area because visualization can help in the development, exploration, verification, and comprehension of ontologies. This paper introduces the design of a new ontology visualization tool, which differs from traditional visualization tools by providing important metrics and analytics about ontology concepts and warning the ontology developer about potential ontology design errors. The tool, called Onyx, also has advantages in terms of speed and readability. Thus, Onyx offers a suitable environment for the representation of large ontologies, especially those used in biomedical and health information systems and those that contain many terms. It is clear that these additional functionalities will increase the value of traditional ontology visualization tools during ontology exploration and evaluation.     

Enabling Cross-Disciplinary E-Science by Integrating Geoscience Ontologies with Dolce

E-Science is increasingly being used to address scientific problems that require cross-disciplinary knowledge, such as climate change, natural disasters, and environmental health. However, the ontologies used to represent scientific knowledge are largely unidisciplinary and need to be integrated to enable big e-Science. The authors investigate the potential of the Dolce foundational ontology to aid the integration of two geoscientific knowledge representations, the Sweet ontology and the GeoSciML schema, to meet the requirements of a cross-disciplinary use case focused on groundwater pollution estimation. They connected the domain ontologies via the foundational ontology, leading to new and improved relations between the domain ontologies that enabled satisfaction of the use case. Although the integrated ontology, called Dolce Rocks, contains some semantic inconsistencies resulting from incompatibilities among the ontologies, the overall results suggest that foundational ontologies can play an important role in cross-disciplinary e-Science.     

Addressing the Ontology Acquisition Bottleneck Through Reverse Ontological Engineering

The use of ontologies in knowledge engineering arose as a solution to the difficulties associated with acquiring knowledge, commonly referred to as the knowledge acquisition bottleneck. The knowledge-level model represented in an ontology provides a much more structured and principled approach compared with earlier transfer-of-symbolic-knowledge approaches but brings with it a new problem, which can be termed the ontology-acquisition (and maintenance) bottleneck. Each ontological approach offers a different structure, different terms and different meanings for those terms. The unifying theme across approaches is the considerable effort associated with developing, validating and connecting ontologies. We propose an approach to engineering ontologies by retrospectively and automatically discovering them from existing data and knowledge sources in the organization. The method offered assists in the identification of similar and different terms and includes strategies for developing a shared ontology. The approach uses a human-centered, concept-based knowledge processing technique, known as formal concept analysis, to generate an ontology from examples. To assist classification of examples and to identify the salient features of the example, we use a rapid and incremental knowledge acquisition and representation technique, known as ripple-down rules. The method can be used as an alternative or complement to other approaches.     

基于范畴论的本体描述方法

针对各种本体语言在描述本体过程中容易产生理解不一致的问题,利用范畴论的抽象性及图形化表示的优势,提出一种基于范畴论的本体描述方法,并给出了本体、本体映射和本体实例化的范畴论定义,其中本体被描述成范畴中的对象,本体间的映射被描述成范畴中对象间的同态射,本体实例化被描述成范畴间的函子。在此基础上,结合共极限和推出给出本体合并的描述及解释,并证明了本体合并的一些典型性质。     

A semantic metrics suite for evaluating modular ontologies

Ontologies, which are formal representations of knowledge within a domain, can be used for designing and sharing conceptual models of enterprises information for the purpose of enhancing understanding, communication and interoperability. For representing a body of knowledge, different ontologies may be designed. Recently, designing ontologies in a modular manner has emerged for achieving better reasoning performance, more efficient ontology management and change handling. One of the important challenges in the employment of ontologies and modular ontologies in modeling information within enterprises is the evaluation of the suitability of an ontology for a domain and the performance of inference operations over it. In this paper, we present a set of semantic metrics for evaluating ontologies and modular ontologies. These metrics measure cohesion and coupling of ontologies, which are two important notions in the process of assessing ontologies for enterprise modeling. The proposed metrics are based on semantic-based definitions of relativeness, and dependencies between local symbols, and also between local and external symbols of ontologies. Based on these semantic definitions, not only the explicitly asserted knowledge in ontologies but also the implied knowledge, which is derived through inference, is considered for the sake of ontology assessment. We present several empirical case studies for investigating the correlation between the proposed metrics and reasoning performance, which is an important issue in applicability of employing ontologies in real-world information systems.     

Using OWL-VisMod through a decision-making process for reusing OWL ontologies

Knowledge representation (KR) can be defined as a set of ontological commitments, provided with the capabilities of performing inference. The knowledge can be represented using an ontology, which provides a shared insight into a certain domain. The use of ontologies to represent knowledge also allows interoperation among knowledge-based systems. The process of building ontologies can be tedious and sometimes exhaustive. A possible solution in order to avoid this problem would be to reuse the ontologies previously created by others. This paper describes a case study of reusability using OWL-VisMod, a tool designed for developing ontological engineering based on visual conceptual modelling for OWL ontologies. A workflow performed with OWL-VisMod is described; including a decision-making process in order to decide whether or not it could be desirable to reuse an ontology, according to the requirements of a certain project.     

Web Authoring for Accessibility (WAfA)

Conventional thought from the Semantic Web community equates the use of ontologies with the representation of the meaning of content. Here, we skew this viewpoint by describing our ontology, Web Authoring for Accessibility (WAfA), which investigates the way ontologies can describe the semantic structure of documents. By understanding the way heterogeneous XHTML (Extensible Hypertext Mark-up Language) documents are structured we can better transform documents, currently inaccessible to visually impaired users. WAfA performs two tasks: (1) it allows us to flexibly model an XHTML document within the context of navigation and orientation through the Web resource; (2) it enables non-expert users to quickly annotate a Web document by providing a ‘lingua franca’ between author and Web Accessibility Domain Experts. Here we describe our ontology, its use, novelty, and importance.     

Protus 2.0: Ontology-based semantic recommendation in programming tutoring system

With the development of the Semantic web the use of ontologies as a formalism to describe knowledge and information in a way that can be shared on the web is becoming common. The explicit conceptualization of system components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration and construction of knowledge rich and intensive systems. Semantic web provides huge potential and opportunities for developing the next generation of e-learning systems. In previous work, we presented tutoring system named Protus (PRogramming TUtoring System) that is used for learning the essence of Java programming language. It uses principles of learning style identification and content recommendation for course personalization. This paper presents new approach to perform effective personalization highly based on Semantic web technologies performed in new version of the system, named Protus 2.0. This comprises the use of an ontology and adaptation rules for knowledge representation and inference engines for reasoning. Functionality, structure and implementation of a Protus 2.0 ontology as well as syntax of SWRL rules implemented for on-the-fly personalization will be presented in this paper.     

基于本体映射的多本体查询方法

随着语义网的发展,本体已经成为很多领域表达知识的主要手段。许多领域都根据自己的需求建立了本体来描述本领域内的知识。但是目前许多针对本体的语义查询只能对一个本体进行查询。为了实现一个查询能够对多个本体进行访问并且返回适当的查询结果,文中提出了一种利用本体映射实现对多本体的查询方法。其中的映射方法是一种基于语义的多策略结合方式。通过实验发现查询的速度与本体的数量基本呈线性关系且不会因为本体异构程度而增加。     

ADOL: a novel framework for automatic domain ontology learning

Ontology, as a semantic representation of a shared conceptualization, makes knowledge machine-readable and easy to spread. One of its typical applications is used to develop e-learning systems with Educational Ontology. Ontology can help students master knowledge architecture of required subjects and make scattered courseware more systematic. A big challenge is how to construct Educational Ontology to describe systematic knowledge of different subjects automatically. Currently, most of the ontologies are developed and extended manually, which requires the developers to possess certain professional knowledge and is time-consuming. In this paper, a framework to construct and extend Educational Ontology automatically is proposed.2 The proposed ontology learning framework, called ‘ADOL,’ can convert domain textbooks into a corresponding ontology automatically and efficiently. A case study on High School Physics shows that our approach is feasible and efficient.

     

Experimentation with local consensus ontologies with implications for automated service composition

Agent technologies represent a promising approach for the integration of interorganizational capabilities across distributed, networked environments. However, knowledge sharing interoperability problems can arise when agents incorporating differing ontologies try to synchronize their internal information. Moreover, in practice, agents may not have a common or global consensus ontology that will facilitate knowledge sharing and integration of functional capabilities. We propose a method to enable agents to develop a local consensus ontology during operation time as needed. By identifying similarities in the ontologies of their peer agents, a set of agents can discover new concepts/relations and integrate them into a local consensus ontology on demand. We evaluate this method, both syntactically and semantically, when forming local consensus ontologies with and without the use of a lexical database. We also report on the effects when several factors, such as the similarity measure, the relation search level depth, and the merge order, are varied. Finally, experimenting in the domain of agent-supported Web service composition, we demonstrate how our method allows us to successfully autonomously form service-oriented local consensus ontologies.