Ontologies: State of the Art, Business Potential, and Grand Challenges (original) (raw)
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Ontology Engineering: From an Art to a Craft
Lecture Notes in Computer Science, 2016
In this paper, we report on our experience and discuss the problems we encountered while designing, implementing and revising a set of ontologies describing the domain of data mining. We focus on a set of key issues that we think are important and need to be addressed by the ontology engineering community. These include ontology evaluation, testing, versioning, the use of design patterns, the use of IT portal(s), re-usability, and compatibility. To illustrate the key issues we provide examples that originate from our work on the ontologies for data mining. We conclude the paper with a summary and some suggestions that we believe should be addressed by the ontology engineering research community.
Ontology Theory, Management and Design
2010
Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Ontology theory, management, and design : advanced tools and models / Faiez Gargouri and Wassim Jaziri, editors. p. cm. Includes bibliographical references and index. Summary: "The focus of this book is on information and communication sciences, computer science, and artificial intelligence and provides readers with access to the latest knowledge related to design, modeling and implementation of ontologies"-Provided by publisher.
The State of the Art in Ontology Design: A Survey and Comparative Review
Ai Magazine, 1997
s In this article, we develop a framework for comparing ontologies and place a number of the more prominent ontologies into it. We have selected 10 specific projects for this study, including general ontologies, domain-specific ones, and one knowledge representation system. The comparison framework includes general characteristics, such as the purpose of an ontology, its coverage (general or domain specific), its size, and the formalism used. It also includes the design process used in creating an ontology and the methods used to evaluate it. Characteristics that describe the content of an ontology include taxonomic organization, types of concept covered, top-level divisions, internal structure of concepts, representation of part-whole relations, and the presence and nature of additional axioms. Finally, we consider what experiments or applications have used the ontologies. Knowledge sharing and reuse will require a common framework to support interoperability of independently created ontologies. Our study shows there is great diversity in the way ontologies are designed and the way they represent the world. By identifying the similarities and differences among existing ontologies, we clarify the range of alternatives in creating a standard framework for ontology design.
Dagstuhl Seminars, 2003
Ontologies have moved beyond the domains of library science, philosophy, and knowledge representation. They are now the concerns of marketing departments, CEOs, and mainstream business. Research analyst companies such as Forrester Research report on the critical roles of ontologies in support of browsing and search for e-commerce and in support of interoperability for facilitation of knowledge management and configuration. One
Ontology development 101: A guide to creating your first ontology
2001
In recent years the development of ontologies-explicit formal specifications of the terms in the domain and relations among them (Gruber 1993)-has been moving from the realm of Artificial-Intelligence laboratories to the desktops of domain experts. Ontologies have become common on the World-Wide Web. The ontologies on the Web range from large taxonomies categorizing Web sites (such as on Yahoo!) to categorizations of products for sale and their features (such as on Amazon.com). The WWW Consortium (W3C) is developing the Resource Description Framework (Brickley and Guha 1999), a language for encoding knowledge on Web pages to make it understandable to electronic agents searching for information. The Defense Advanced Research Projects Agency (DARPA), in conjunction with the W3C, is developing DARPA Agent Markup Language (DAML) by extending RDF with more expressive constructs aimed at facilitating agent interaction on the Web (Hendler and McGuinness 2000). Many disciplines now develop standardized ontologies that domain experts can use to share and annotate information in their fields. Medicine, for example, has produced large, standardized, structured vocabularies such as SNOMED (Price and Spackman 2000) and the semantic network of the Unified Medical Language System (Humphreys and Lindberg 1993). Broad general-purpose ontologies are emerging as well. For example, the United Nations Development Program and Dun & Bradstreet combined their efforts to develop the UNSPSC ontology which provides terminology for products and services (www.unspsc.org). An ontology defines a common vocabulary for researchers who need to share information in a domain. It includes machine-interpretable definitions of basic concepts in the domain and relations among them. Why would someone want to develop an ontology? Some of the reasons are: • To share common understanding of the structure of information among people or software agents • To enable reuse of domain knowledge • To make domain assumptions explicit • To separate domain knowledge from the operational knowledge • To analyze domain knowledge
Ontologies: Principles, methods and applications
The Knowledge Engineering …, 2009
This paper is intended to serve as a comprehensive introduction to the emerging field concerned with the design and use of ontologies. We observe that disparate backgrounds, languages, tools and techniques are a major barrier to effective communication among people, ...
Tutorial on ontological engineering Part 2: Ontology development, tools and languages
New Generation Computing, 2004
This tutorial course describes the current state of the art of ontological engineering which is a successor of knowledge engineering. It covers theory, tools and applications and consists of three parts: Part 1 is an introduction to ontological engineering, Part 2 describes ontology development, languages and tools, and Part 3 is an advanced course dealing with philosophical issues of ontology design together with detailed guidelines of ontology development. Part 3 also presents a success story of ontological engineering with the deployment result in a company. The philosophy behind this tutorial is that ontological engineering is viewed as a challenge to enabling knowledge sharing and reuse which knowledge engineering failed to realize. Therefore, one of the major topics dealt with in this tutorial is to explain what an ontology should be while explaining how it is understood currently.
Synthesis Lectures on the Semantic Web: Theory and Technology, 2019
Whether you call it the Semantic Web, Linked Data, or Web 3.0, a new generation of Web technologies is offering major advances in the evolution of the World Wide Web. As the first generation of this technology transitions out of the laboratory, new research is exploring how the growing Web of Data will change our world. While topics such as ontology-building and logics remain vital, new areas such as the use of semantics in Web search, the linking and use of open data on the Web, and future applications that will be supported by these technologies are becoming important research areas in their own right. Whether they be scientists, engineers or practitioners, Web users increasingly need to understand not just the new technologies of the Semantic Web, but to understand the principles by which those technologies work, and the best practices for assembling systems that integrate the different languages, resources, and functionalities that will be important in keeping the Web the rapidly expanding, and constantly changing, information space that has changed our lives. Topics to be included: • Semantic Web Principles from linked-data to ontology design • Key Semantic Web technologies and algorithms • Semantic Search and language technologies • The Emerging "Web of Data" and its use in industry, government and university applications • Trust, Social networking and collaboration technologies for the Semantic Web • The economics of Semantic Web application adoption and use iv • Publishing and Science on the Semantic Web • Semantic Web in health care and life sciences Ontology Engineering
Ontology Engineering and Development Aspects: A Survey
International Journal of Education and Management Engineering, 2016
Ontology can be defined as hierarchical representation of classes, sub classes, their properties and instances. It has led to understanding the concepts of given domain, deriving relationships and representing them in machine interpretable language. Ontologies are associated with different languages that are used in mapping of multiple ontologies. Several applications of ontologies have led towards realization of semantic web. The current web (2.0) is approaching towards semantic web (3.0) that performs intelligent search and stores results in distributed databases. The paper makes readers aware of various aspects of ontology like types of ontology, ontology development life cycle phases, activities involved in ontology development and ontology engineering tools. Ontology engineering contributes to meaningful search and provides with open source tools for deploying and building ontologies.