scispace - formally typeset
Open Access

OntoQA: Metric-Based Ontology Quality Analysis

Reads0
Chats0
TLDR
OntoQA, an approach that analyzes ontology schemas and their populations (i.e. knowledgebases) and describes them through a well defined set of metrics can highlight key characteristics of an ontology schema as well as its population and enable users to make an informed decision quickly.
Abstract
As the Semantic Web gains importance for sharing knowledge on the Internet this has lead to the development and publishing of many ontologies in different domains. When trying to reuse existing ontologies into their applications, users are faced with the problem of determining if an ontology is suitable for their needs. In this paper, we introduce OntoQA, an approach that analyzes ontology schemas and their populations (i.e. knowledgebases) and describes them through a well defined set of metrics. These metrics can highlight key characteristics of an ontology schema as well as its population and enable users to make an informed decision quickly. We present an evaluation of several ontologies using these metrics to demonstrate their applicability.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO

TL;DR: Data quality criteria according to which KGs can be analyzed and analyze and compare the above mentioned KGs are provided and a framework for finding the most suitable KG for a given setting is proposed.
BookDOI

Ontology Engineering in a Networked World

TL;DR: This book by Surez-Figueroa et al. provides the necessary methodological and technological support for the development and use of ontology networks, which ontology developers need in this distributed environment.
Journal ArticleDOI

Ontology-based models in pervasive computing systems

TL;DR: This work identifies a number of deficiencies that must be addressed in order to apply the ontological techniques successfully to next-generation pervasive systems.
Book ChapterDOI

Characterizing the semantic web on the web

TL;DR: A collection of Semantic Web documents from an estimated ten million available on the Web is harvested and analyzed, and a number of metrics, properties and usage patterns found to follow a power law distribution are described.
Book ChapterDOI

Ontological Evaluation and Validation

TL;DR: This chapter introduces several approaches that have been developed to aid in evaluating ontologies, and presents highlights of OntoQA, an ontology evaluation and analysis tool that uses a set of metrics measuring different aspects of the ontology schema and knowledgebase to give an insight to the overall characteristics of the Ontology.
References
More filters

Ontology Development 101: A Guide to Creating Your First Ontology

TL;DR: An ontology defines a common vocabulary for researchers who need to share information in a domain that includes machine-interpretable definitions of basic concepts in the domain and relations among them.
Book ChapterDOI

Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema

TL;DR: This work presents an overview of Sesame, an architecture for efficient storage and expressive querying of large quantities of metadata in RDF and RDF Schema, and its implementation and the first experiences with this implementation.
Journal ArticleDOI

The State of the Art in Ontology Design: A Survey and Comparative Review

Natalya F. Noy, +1 more
- 15 Sep 1997 - 
TL;DR: A framework for comparing ontologies is developed and a number of the more prominent ontologies are placed into it and clarified the range of alternatives in creating a standard framework for ontology design is clarified.
Journal ArticleDOI

ONTOMETRIC: A Method to Choose the Appropriate Ontology

TL;DR: This work proposes a method, ONTOMETRIC, which allows the users to measure the suitability of existing ontologies, regarding the requirements of their systems.
Related Papers (5)