An Automated System for the Assessment and Ranking of Domain Ontologies

As the number of intelligent software applications and the number of semantic websites continue to expand, ontologies are needed to formalize shared terms. Often it is necessary to either find a previously used ontology for a particular purpose, or to develop a new one to meet a specific need. Because of the challenge involved in creating a new ontology from scratch, the latter option is often preferable. The ability of a user to select an appropriate, high-quality domain ontology from a set of available options would be most useful in knowledge engineering and in developing intelligent applications. Being able to assess an ontology\u27s quality and suitability is also important when an ontology is developed from the beginning. These capabilities, however, require good quality assessment mechanisms as well as automated support when there are a large number of ontologies from which to make a selection. This thesis provides an in-depth analysis of the current research in domain ontology evaluation, including the development of a taxonomy to categorize the numerous directions the research has taken. Based on the lessons learned from the literature review, an approach to the automatic assessment of domain ontologies is selected and a suite of ontology quality assessment metrics grounded in semiotic theory is presented. The metrics are implemented in a Domain Ontology Rating System (DoORS), which is made available as an open source web application. An additional framework is developed that would incorporate this rating system as part of a larger system to find ontology libraries on the web, retrieve ontologies from them, and assess them to select the best ontology for a particular task. An empirical evaluation in four phases shows the usefulness of the work, including a more stringent evaluation of the metrics that assess how well an ontology fits its domain and how well an ontology is regarded within its community of users

An ontology knowledge inspection methodology for quality assessment and continuous improvement

Ontology-learning methods were introduced in the knowledge engineering area to automatically build ontologies from natural language texts related to a domain. Despite the initial appeal of these methods, automatically generated ontologies may have errors, inconsistencies, and a poor design quality, all of which must be manually fixed, in order to maintain the validity and usefulness of automated output. In this work, we propose a methodology to assess ontologies quality (quantitatively and graphically) and to fix ontology inconsistencies minimising design defects. The proposed methodology is based on the Deming cycle and is grounded on quality standards that proved effective in the software engineering domain and present high potential to be extended to knowledge engineering quality management. This paper demonstrates that software engineering quality assessment approaches and techniques can be successfully extended and applied to the ontology-fixing and quality improvement problem. The proposed methodology was validated in a testing ontology, by ontology design quality comparison between a manually created and automatically generated ontology.info:eu-repo/semantics/publishedVersio

Architecture and usability of OntoKeeper, an ontology evaluation tool

Abstract Background The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automated tools may help to ease the ontology construction, maintenance, assessment and quality assurance processes. However, there are relatively few tools that exist that can provide this support to knowledge engineers. Method We introduce OntoKeeper as a web-based tool that can automate quality scoring for ontology developers. We enlisted 5 experienced ontologists to test the tool and then administered the System Usability Scale to measure their assessment. Results In this paper, we present usability results from 5 ontologists revealing high system usability of OntoKeeper, and use-cases that demonstrate its capabilities in previous published biomedical ontology research. Conclusion To the best of our knowledge, OntoKeeper is the first of a few ontology evaluation tools that can help provide ontology evaluation functionality for knowledge engineers with good usability.https://deepblue.lib.umich.edu/bitstream/2027.42/152214/1/12911_2019_Article_859.pd

Konseptualisasi Ontologi Iklan Website

Abstract. The high internet users in Indonesia, with a number of user penetration of more than 34.9%. The internet user has a diverse demographic that is spread throughout the territory. Seeing this potential can be in the know on the website advertising potential. To optimize that ads on a website can be relevant to the user required a design method. Ontologies are used as domain knowledge in the delivery of relevant ads. Ontology is built through a process of conceptualization, adapted from methods Gruninger and Fox and Methontology. Conceptualization resulting from such methods, evaluation methods OntoQA (Ontology Quality Analysis). Measurements were carried out to produce a quality score potential knowledge with details Relation richness value of 0.451, the value of Inheritance richness of 4.857 and a richness Attributte value of 6.75. Value Relations shows the richness of the information provided ontology categorized at level sufficiently rich in knowledge. Value Inheritance richness showed ontology includes areas of general knowledge. While the value Attributte describe the richness of the information provided.Keywords: Ontology, Ads, OntQA Abstrak. Tingginya pengguna internet di indonesia, dengan jumlah penetrasi pengguna lebih dari 34,9%. Pengguna internet tersebut memiliki demografi beraneka ragam yang tersebar diseluruh wilayah. Melihat hal tersebut dapat di ketahui potensi iklan pada website sangat potensial. Untuk mengoptimalkan agar iklan yang ada pada sebuah website dapat relevan dengan pengguna diperlukan sebuah metode perancangan. Ontologi dimanfaatkan sebagai domain pengetahuan dalam pemberian iklan yang relevan. Ontologi dibangun melalui proses konseptualisasi yang diadaptasi dari metode Gruninger and Fox dan Methontology. Konseptualisasi yang dihasilkan dari metode tersebut, dilakukan evaluasi menggunakan metode OntoQA (Ontology Quality Analysis). Pengukuran yang dilakukan menghasilkan skor kualitas potensi pengetahuan dengan rincian nilai Relation Richness sebesar 0,452, nilai Inheritance Richness sebesar 4,857 dan nilai Attributte Richness sebesar 6,75. Nilai Relation Richness menunjukkan informasi yang disediakan ontologi dikategorikan pada level cukup kaya akan pengetahuan. Nilai Inheritance Richness menunjukkan ontologi mencakup bidang pengetahuan yang umum. Sementara nilai Attributte Richness menggambarkan informasi yang disediakan.Kata Kunci: Ontologi, Iklan, OntoQ

Using Semantic Technologies in Digital Libraries- A Roadmap to Quality Evaluation

Abstract. In digital libraries semantic techniques are often deployed to reduce the expensive manual overhead for indexing documents, maintaining metadata, or caching for future search. However, using such techniques may cause a decrease in a collection’s quality due to their statistical nature. Since data quality is a major concern in digital libraries, it is important to be able to measure the (loss of) quality of metadata automatically generated by semantic techniques. In this paper we present a user study based on a typical semantic technique use

A strategy for analyzing and enriching domain ontologies

During the last years there is an increasing interest on the ontologies. The way in which the semantics of a domain entity is represented in an ontology may di er depending on the requirements that the ontology should satisfy. However, in general the richness is a desired quality attribute for an ontology. The contribution of this paper is a strategy for evaluating and enriching the representation of real entity semantics in a domain ontology. In addition, an application example is discussed.Presentado en el II Workshop Innovación en Sistemas de Software (WISS)Red de Universidades con Carreras en Informática (RedUNCI

Repairing Ontologies via Axiom Weakening.

Ontology engineering is a hard and error-prone task, in which small changes may lead to errors, or even produce an inconsistent ontology. As ontologies grow in size, the need for automated methods for repairing inconsistencies while preserving as much of the original knowledge as possible increases. Most previous approaches to this task are based on removing a few axioms from the ontology to regain consistency. We propose a new method based on weakening these axioms to make them less restrictive, employing the use of refinement operators. We introduce the theoretical framework for weakening DL ontologies, propose algorithms to repair ontologies based on the framework, and provide an analysis of the computational complexity. Through an empirical analysis made over real-life ontologies, we show that our approach preserves significantly more of the original knowledge of the ontology than removing axioms

The evaluation of ontologies: quality, reuse and social factors

Finding a “good” or the “right” ontology is a growing challenge in the ontology domain, where one of the main aims is to share and reuse existing semantics and knowledge. Before reusing an ontology, knowledge engineers not only have to find a set of appropriate ontologies for their search query, but they should also be able to evaluate those ontologies according to different internal and external criteria. Therefore, ontology evaluation is at the heart of ontology selection and has received a considerable amount of attention in the literature.Despite the importance of ontology evaluation and selection and the widespread research on these topics, there are still many unanswered questions and challenges when it comes to evaluating and selecting ontologies for reuse. Most of the evaluation metrics and frameworks in the literature are mainly based on a limited set of internal characteristics, e.g., content and structure of ontologies and ignore how they are used and evaluated by communities. This thesis aimed to investigate the notion of quality and reusability in the ontology domain and to explore and identify the set of metrics that can affect the process of ontology evaluation and selection for reuse. [Continues.