Completion of Ontologies and Ontology Networks


Book Description

The World Wide Web contains large amounts of data, and in most cases this data has no explicit structure. The lack of structure makes it difficult for automated agents to understand and use such data. A step towards a more structured World Wide Web is the Semantic Web, which aims at introducing semantics to data on the World Wide Web. One of the key technologies in this endeavour are ontologies, which provide a means for modeling a domain of interest and are used for search and integration of data. In recent years many ontologies have been developed. To be able to use multiple ontologies it is necessary to align them, i.e., find inter-ontology relationships. However, developing and aligning ontologies is not an easy task and it is often the case that ontologies and their alignments are incorrect and incomplete. This can be a problem for semantically-enabled applications. Incorrect and incomplete ontologies and alignments directly influence the quality of the results of such applications, as wrong results can be returned and correct results can be missed. This thesis focuses on the problem of completing ontologies and ontology networks. The contributions of the thesis are threefold. First, we address the issue of completing the is-a structure and alignment in ontologies and ontology networks. We have formalized the problem of completing the is-a structure in ontologies as an abductive reasoning problem and developed algorithms as well as systems for dealing with the problem. With respect to the completion of alignments, we have studied system performance in the Ontology Alignment Evaluation Initiative, a yearly evaluation campaign for ontology alignment systems. We have also addressed the scalability of ontology matching, which is one of the current challenges, by developing an approach for reducing the search space when generating the alignment.Second, high quality completion requires user involvement. As users' time and effort are a limited resource we address the issue of limiting and facilitating user interaction in the completion process. We have conducted a broad study of state-of-the-art ontology alignment systems and identified different issues related to the process. We have also conducted experiments to assess the impact of user errors in the completion process. While the completion of ontologies and ontology networks can be done at any point in the life-cycle of ontologies and ontology networks, some of the issues can be addressed already in the development phase. The third contribution of the thesis addresses this by introducing ontology completion and ontology alignment into an existing ontology development methodology.




NeOn Methodology for Building Ontology Networks


Book Description

A new ontology development paradigm has started its emphasis lies on the reuse and possible subsequent reengineering of knowledge resources, on the collaborative and argumentative ontology development, and on the building of ontology networks this new trend is the opposite of building new ontologies from scratch. To help ontology developers in this new paradigm, it is important to provide strong methodological support.However, up to date, there are no methodological approaches that help ontology developers to build large ontologies embedded in ontology networks in complex settings where distributed teams could




Ontology in Information Science


Book Description

The book on Ontology in Information Science explores a broad set of ideas and presents some of the state-of-the-art research in this field concisely in 12 chapters. This book provides researchers and practitioners working in the field of ontology and information science an opportunity to share their theories, methodologies, experiences, and experimental results related to ontology development and application in various areas. It also includes the design aspects of domain ontologies considering the architecture, development strategy, and selection of tools. The intended audience of this book will mainly consist of researchers, research students, and practitioners in the field of ontology and information science.




Ontology-Based Information Retrieval for Healthcare Systems


Book Description

With the advancements of semantic web, ontology has become the crucial mechanism for representing concepts in various domains. For research and dispersal of customized healthcare services, a major challenge is to efficiently retrieve and analyze individual patient data from a large volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for clinical information systems so that the pertinent information can be mined from large amount of distributed data. This unique and groundbreaking book highlights the key advances in ontology-based information retrieval techniques being applied in the healthcare domain and covers the following areas: Semantic data integration in e-health care systems Keyword-based medical information retrieval Ontology-based query retrieval support for e-health implementation Ontologies as a database management system technology for medical information retrieval Information integration using contextual knowledge and ontology merging Collaborative ontology-based information indexing and retrieval in health informatics An ontology-based text mining framework for vulnerability assessment in health and social care An ontology-based multi-agent system for matchmaking patient healthcare monitoring A multi-agent system for querying heterogeneous data sources with ontologies for reducing cost of customized healthcare systems A methodology for ontology based multi agent systems development Ontology based systems for clinical systems: validity, ethics and regulation




Ontologies for Software Engineering and Software Technology


Book Description

This book covers two applications of ontologies in software engineering and software technology: sharing knowledge of the problem domain and using a common terminology among all stakeholders; and filtering the knowledge when defining models and metamodels. By presenting the advanced use of ontologies in software research and software projects, this book is of benefit to software engineering researchers in both academia and industry.




An Introduction to Ontology Engineering


Book Description

An Introduction to Ontology Engineering introduces the student to a comprehensive overview of ontology engineering, and offers hands-on experience that illustrate the theory. The topics covered include: logic foundations for ontologies with languages and automated reasoning, developing good ontologies with methods and methodologies, the top-down approach with foundational ontologies, and the bottomup approach to extract content from legacy material, and a selection of advanced topics that includes Ontology-Based Data Access, the interaction between ontologies and natural languages, and advanced modelling with fuzzy and temporal ontologies. Each chapter contains review questions and exercises, and descriptions of two group assignments are provided as well. The textbook is aimed at advanced undergraduate/postgraduate level in computer science and could fi t a semester course in ontology engineering or a 2-week intensive course. Domain experts and philosophers may fi nd a subset of the chapters of interest, or work through the chapters in a different order. Maria Keet is an Associate Professor with the Department of Computer Science, University of Cape Town, South Africa. She received her PhD in Computer Science in 2008 at the KRDB Research Centre, Free University of Bozen-Bolzano, Italy. Her research focus is on knowledge engineering with ontologies and Ontology, and their interaction with natural language and conceptual data modelling, which has resulted in over 100 peer-reviewed publications. She has developed and taught multiple courses on ontology engineering and related courses at various universities since 2009.




Fostering User Involvement in Ontology Alignment and Alignment Evaluation


Book Description

The abundance of data at our disposal empowers data-driven applications and decision making. The knowledge captured in the data, however, has not been utilized to full potential, as it is only accessible to human interpretation and data are distributed in heterogeneous repositories. Ontologies are a key technology unlocking the knowledge in the data by providing means to model the world around us and infer knowledge implicitly captured in the data. As data are hosted by independent organizations we often need to use several ontologies and discover the relationships between them in order to support data and knowledge transfer. Broadly speaking, while ontologies provide formal representations and thus the basis, ontology alignment supplies integration techniques and thus the means to turn the data kept in distributed, heterogeneous repositories into valuable knowledge. While many automatic approaches for creating alignments have already been developed, user input is still required for obtaining the highest-quality alignments. This thesis focuses on supporting users during the cognitively intensive alignment process and makes several contributions. We have identified front- and back-end system features that foster user involvement during the alignment process and have investigated their support in existing systems by user interface evaluations and literature studies. We have further narrowed down our investigation to features in connection to the, arguably, most cognitively demanding task from the users’ perspective—manual validation—and have also considered the level of user expertise by assessing the impact of user errors on alignments’ quality. As developing and aligning ontologies is an error-prone task, we have focused on the benefits of the integration of ontology alignment and debugging. We have enabled interactive comparative exploration and evaluation of multiple alignments at different levels of detail by developing a dedicated visual environment—Alignment Cubes—which allows for alignments’ evaluation even in the absence of reference alignments. Inspired by the latest technological advances we have investigated and identified three promising directions for the application of large, high-resolution displays in the field: improving the navigation in the ontologies and their alignments, supporting reasoning and collaboration between users.




Content Ontology Design Patterns: Qualities, Methods, and Tools


Book Description

Ontologies are formal knowledge models that describe concepts and relationships and enable data integration, information search, and reasoning. Ontology Design Patterns (ODPs) are reusable solutions intended to simplify ontology development and support the use of semantic technologies by ontology engineers. ODPs document and package good modelling practices for reuse, ideally enabling inexperienced ontologists to construct high-quality ontologies. Although ODPs are already used for development, there are still remaining challenges that have not been addressed in the literature. These research gaps include a lack of knowledge about (1) which ODP features are important for ontology engineering, (2) less experienced developers' preferences and barriers for employing ODP tooling, and (3) the suitability of the eXtreme Design (XD) ODP usage methodology in non-academic contexts. This dissertation aims to close these gaps by combining quantitative and qualitative methods, primarily based on five ontology engineering projects involving inexperienced ontologists. A series of ontology engineering workshops and surveys provided data about developer preferences regarding ODP features, ODP usage methodology, and ODP tooling needs. Other data sources are ontologies and ODPs published on the web, which have been studied in detail. To evaluate tooling improvements, experimental approaches provide data from comparison of new tools and techniques against established alternatives. The analysis of the gathered data resulted in a set of measurable quality indicators that cover aspects of ODP documentation, formal representation or axiomatisation, and usage by ontologists. These indicators highlight quality trade-offs: for instance, between ODP Learnability and Reusability, or between Functional Suitability and Performance Efficiency. Furthermore, the results demonstrate a need for ODP tools that support three novel property specialisation strategies, and highlight the preference of inexperienced developers for template-based ODP instantiation---neither of which are supported in prior tooling. The studies also resulted in improvements to ODP search engines based on ODP-specific attributes. Finally, the analysis shows that XD should include guidance for the developer roles and responsibilities in ontology engineering projects, suggestions on how to reuse existing ontology resources, and approaches for adapting XD to project-specific contexts.




Applied Ontology


Book Description

Ontology is the philosophical discipline which aims to understand how things in the world are divided into categories and how these categories are related together. This is exactly what information scientists aim for in creating structured, automated representations, called ‘ontologies,’ for managing information in fields such as science, government, industry, and healthcare. Currently, these systems are designed in a variety of different ways, so they cannot share data with one another. They are often idiosyncratically structured, accessible only to those who created them, and unable to serve as inputs for automated reasoning. This volume shows, in a non-technical way and using examples from medicine and biology, how the rigorous application of theories and insights from philosophical ontology can improve the ontologies upon which information management depends.




Introduction to Bio-Ontologies


Book Description

Introduction to Bio-Ontologies explores the computational background of ontologies. Emphasizing computational and algorithmic issues surrounding bio-ontologies, this self-contained text helps readers understand ontological algorithms and their applications.The first part of the book defines ontology and bio-ontologies. It also explains the importan