The State of the Art in Ontology Design: A Survey and Comparative Review (original) (raw)
Related papers
A Study Investigating Typical Concepts and Guidelines for Ontology Building
2015
In semantic technologies, the shared common understanding of the structure of information among artifacts (people or software agents) can be realized by building an ontology. To do this, it is imperative for an ontology builder to answer several questions: a) what are the main components of an ontology? b) How an ontology look likes and how it works? c) Verify if it is required to consider reusing existing ontologies or not? c) What is the complexity of the ontology to be developed? d) What are the principles of ontology design and development? e) How to evaluate an ontology? This paper answers all the key questions above. The aim of this paper is to present a set of guiding principles to help ontology developers and also inexperienced users to answer such questions.
International Journal of Information Engineering and Electronic Business, 2020
The success of machine represented web known as semantic web largely hinges on ontologies. Ontology is a data modeling technique for structured data repository premised on collection of concepts with their semantic relationships and constraints on domain. There are existing methodologies to aid ontology development process. However, there is no single correct ontology design methodology. Therefore, this paper aims to present a review on existing ontology development approaches for different domains with the goal of identifying individual methodology's weakness and suggests for hybridization in order to strengthen ontology development in terms of its content and constructions correctness. The analysis and comparison of the review were carried out by considering these criteria but not limited to: activities of each method, the initial domain of the methodology, ontology created from scratch or reuse, frequently used ontology management tools based on literature, subject granularity, and usage across different platforms. This review based on the literature showed some approaches that exhibit the required principles of ontology engineering in tandem with software development principles. Nonetheless, the review still noted some gaps among the methodologies that when bridged or hybridized a better correctness of ontology development would be achieved in building intelligent system.
Ontologies: State of the Art, Business Potential, and Grand Challenges
Computing for Human Experience, 2008
In this chapter, we give an overview of what ontologies are and how they can be used. We discuss the impact of the expressiveness, the number of domain elements, the community size, the conceptual dynamics, and other variables on the feasibility of an ontology project. Then, we break down the general promise of ontologies of facilitating the exchange and usage of knowledge to six distinct technical advancements that ontologies actually provide, and discuss how this should influence design choices in ontology projects. Finally, we summarize the main challenges of ontology management in real-world applications, and explain which expectations from practitioners can be met as of today.
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
Toward principles for the design of ontologies used for knowledge sharing?
International Journal of Human-computer Studies / International Journal of Man-machine Studies, 1995
Recent work in Artificial Intelligence (AI) is exploring the use of formal ontologies as a way of specifying content-specific agreements for the sharing and reuse of knowledge among software entities. We take an engineering perspective on the development of such ontologies. Formal ontologies are viewed as designed artifacts, formulated for specific purposes and evaluated against objective design criteria. We describe the role of ontologies in supporting knowledge sharing activities, and then present a set of criteria to guide the development of ontologies for these purposes. We show how these criteria are applied in case studies from the design of ontologies for engineering mathematics and bibliographic data. Selected design decisions are discussed, and alternative representation choices are evaluated against the design criteria.
IEEE Access, 2021
Interlocking Institutional Worlds (IWs) is a concept explaining the need to interoperate between institutions (or players), to solve problems of common interest in a given domain. Managing knowledge in the IWs domain is complex; however, promoting knowledge sharing based on standards and common terms agreeable to all players is essential and is something that must be established. In this context, ontologies, as a conceptual tool and a key component of knowledge-based systems, have been used by organizations for effective knowledge management, better decision-making, and interoperability among diverse institutions of an IWs domain. The development of ontology involves structural and logical complexity, and requires a well-designed, mature, and widely accepted methodology, to ensure its reliability. Many methodologies for ontology development have been proposed by several researchers; however, most of the developed methodologies have not included several important phases. Furthermore, several methodologies have not provided the complete details of the techniques and activities involved in the ontology construction process. Fewer details make it difficult to follow a methodology for designing ontologies. This study aims to compare existing methodologies based on sixteen important criteria and proposes an improved methodology for ontology development for IWs domains. The proposed methodology has included several important phases such as the Estimation of Human Resources, Re-engineering and Re-using of Resources, Collaborative Ontology Construction,
The evaluation of ontologies: Toward improved semantic interoperability
Semantic Web, 2006
Recent years have seen rapid progress in the development of ontologies as semantic models intended to capture and represent aspects of the real world. There is, however, great variation in the quality of ontologies. If ontologies are to become progressively better in the future, more rigorously developed, and more appropriately compared, then a systematic discipline of ontology evaluation must be created to ensure quality of content and methodology. Systematic methods for ontology evaluation will take into account ...
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.
A Survey on Usage of Ontology in Different Domains
A survey has been presented on the usage of ontology in various domains like Medical, Agriculture, Geosciences, Education, Marine, Communication, Computer, Chemical, Defence, Linguistic etc. A summary of the available ontology developed in various domains is given and no attempt has been made to evaluate them. Only a broad picture of ontology applications in various domains practiced today are described. In some cases details like number of concepts, relationship, classes and subclasses defined are also given. The survey indicated that considerable effort has gone in the development of ontology in the domains of medical, education, computer science. It is noted that rather limited effort has gone into the development of ontology in the domains of power plants and atomic energy.