Ontology Engineering

by Elisa F. Kendall, Deborah McGuinness

Ontologies have become increasingly important as the use of knowledge graphs, machine learning, natural language processing (NLP), and the amount of data generated on a daily basis has exploded. As of 2014, 90% of the data in the digital universe was generated in the two years prior, and the volume of data was projected to grow from 3.2 zettabytes to 40 zettabytes in the next six years. The very real issues that government, research, and commercial organizations are facing in order to sift through this amount of information to support decision-making alone mandate increasing automation. Yet, the data profiling, NLP, and learning algorithms that are ground-zero for data integration, manipulation, and search provide less than satisfactory results unless they utilize terms with unambiguous semantics, such as those found in ontologies and well-formed rule sets. Ontologies can provide a rich "schema" for the knowledge graphs underlying these technologies as well as the terminological and semantic basis for dramatic improvements in results. Many ontology projects fail, however, due at least in part to a lack of discipline in the development process. This book, motivated by the Ontology 101 tutorial given for many years at what was originally the Semantic Technology Conference (SemTech) and then later from a semester-long university class, is designed to provide the foundations for ontology engineering. The book can serve as a course textbook or a primer for all those interested in ontologies.

Hardcover

Published August 15, 2022

Reviews

[Jindřich Mynarz · Rating 3 out of 5]

Most ontologies fail without an understanding of their function. The understanding must be built and described as user requirements, competency questions, or the like.

I appreciate the unrelenting emphasis this books' authors put on requirements and use cases to keep ontologies relevant to their business use.

What drags this book down is lazy editing and typesetting by the publisher, Morgan & Claypool. Given the price of the book I would expect a greater care for the high-quality content it offers.

[Larry · Rating 5 out of 5]

Ontology Engineering is a great companion to "Semantic Web for the Working Ontologist
Effective Modeling in RDFS and OWL" By Dean Allemang, James Hendler.

Deborah McGuinness and Elisa Kendall lead a book club conversation about Ontology Engineering and how ontologies can be used to provide a schema to underpin NLP, search, and overall data profiling, integration, and manipulation. This the wave of the future.

5 weeks for $50 -- tickets here: https://lnkd.in/eGxwr9f

#ontology #datamanagement #NLP #data #knowledgegraphs #kgs

[Jennifer · Rating 3 out of 5]

Interesting text on ontology, language, understanding context, and relationships. It categorizes how we group and classify. This would be very helpful in my engineering classes on conceptual design.