Empirical Ontology Design Patterns

Empirical Ontology Design Patterns
Author :
Publisher : IOS Press
Total Pages : 154
Release :
ISBN-10 : 9781643684796
ISBN-13 : 1643684795
Rating : 4/5 (795 Downloads)

Book Synopsis Empirical Ontology Design Patterns by : V.A. Carriero

Download or read book Empirical Ontology Design Patterns written by V.A. Carriero and published by IOS Press. This book was released on 2024-01-26 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, knowledge graphs (KGs) and ontologies have been widely adopted for modeling many kinds of domain. They are frequently released openly, something which benefits those who are starting new projects, because it offers them a wide choice of ontology reuse and the possibility to link to existing data. Understanding the content of an ontology or a knowledge graph is far from straightforward, however, and existing methods address this issue only partially, while exploring and comparing multiple ontologies can be a tedious manual task. This book, Empirical Ontology Design Patterns, starts from the premise that identifying the Ontology Design Patterns (ODPs) used in an ontology or a knowledge graph will go some way to addressing this problem. Its main focus is to provide tools which will effectively support the task of automatically identifying ODPs in existing ontologies and knowledge graphs. The book analyses the role of ODPs in ontology engineering, placing this analysis in the wider context of existing approaches to ontology reuse and implementation. It introduces a novel method for extracting empirical ontology design patterns (EODPs) from ontologies, and another for extracting EODPs from knowledge graphs whose schemas are implicit. Both methods are applied to ontologies and knowledge graphs frequently adopted and reused, such as Wikidata. The book also offers an ontology which can be used as a basis for annotating ODPs in ontologies and knowledge graphs, whether manually or automatically. The book will be of interest to all those whose work involves the use or reuse of ontologies and knowledge graphs.


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