Title Ontology Engineering
Author Elisa F. Kendall , Deborah L. McGuinness
ISBN 9781681733081
List price USD 49.95
Price outside India Available on Request
Original price
Binding Paperback
No of pages 120
Book size 191 X 235 mm
Publishing year 2019
Original publisher Morgan & Claypool Publishers (Eurospan Group)
Published in India by .
Exclusive distributors Viva Books Private Limited
Sales territory India, Sri Lanka, Bangladesh, Pakistan, Nepal, .
Status New Arrival
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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 had been generated in the preceding two years, and the volume of data was projected to grow from 3.2 zettabytes to 40 zettabytes in the following 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.


Foreword by Dean Allemang

Foreword by Richard Mark Soley, Ph.D.


Chapter 1: Foundations • Background and Definitions • Logic and Ontological Commitment • Ontology-Based Capabilities • Knowledge Representation Languages • Description Logic Languages • Knowledge Bases, Databases, and Ontology • Reasoning, Truth Maintenance, and Negation • Explanations and Proof

Chapter 2: Before You Begin • Domain Analysis • Modeling and Levels of Abstraction • General Approach to Vocabulary Development • Business Vocabulary Development • Evaluating Ontologies • Ontology Design Patterns • Selecting a Language

Chapter 3: Requirements and Use Cases • Getting Started • Gathering References and Potentially Reusable Ontologies • A Bit About Terminology • Summarizing the Use Case • The “Body” of the Use Case • Creating Usage Scenarios • Flow of Events • Competency Questions • Additional Resources • Integration with Business and Software Requirements

Chapter 4: Terminology • How Terminology Work Fits into Ontology Engineering • Laying the Groundwork • Term Excerption and Development • Terminology Analysis and Curation • Concept Labeling • Definitions • Synonyms • Identifiers and Identification Schemes • Classifiers and Classification Schemes • Pedigree and Provenance • Additional Notes (Annotations) • Mapping Terminology Annotations to Standard Vocabularies

Chapter 5: Conceptual Modeling • Overview • Getting Started • Identifying Reusable Ontologies • Preliminary Domain Modeling • Naming Conventions for Web-Based Ontologies • Metadata for Ontologies and Model Elements • General Nature of Descriptions • Relationships and Properties • Individuals and Data Ranges • Other Common Constructs

Chapter 6: Conclusion


Author’s Biographies

About the Authors:

Elisa F. Kendall is a Partner in Thematix Partners LLC and graduate-level lecturer in computer science, focused on data management, data governance, knowledge representation, and decisioning systems. Her consulting practice includes business and information architecture, knowledge representation strategies, and ontology design, development, and training for clients in financial services, government, manufacturing, media, pharmaceutical, and retail domains. Recent projects have focused on use of ontologies to drive natural language processing, machine learning, interoperability, and other knowledge graph-based applications. Elisa represents knowledge representation, ontology, information architecture, and data management concerns on the Object Management Group (OMG)’s Architecture Board, is co-editor of the Ontology Definition Metamodel (ODM), and a contributor to a number of other ISO, W3C, and OMG standards, including the Financial Industry Business Ontology (FIBO) effort. Prior to joining Thematix, she was the founder and CEO of Sandpiper Software, an early entrant in the Semantic Web domain. Earlier in her career, she was software development manager for Aspect Development, and before that a ground systems data processing engineer for Lockheed Martin. She holds a B.S. in Mathematics and Computer Science from UCLA, and an A.M in Linguistics from Stanford University.

Deborah L. McGuinness is the Tetherless World Senior Constellation Chair and Professor of Computer, Cognitive, and Web Sciences at RPI. She is also the founding director of the Web Science Research Center and the CEO of McGuinness Associates Consulting. Deborah has been recognized with awards as a fellow of the American Association for the Advancement of Science (AAAS) for contributions to the Semantic Web, knowledge representation, and reasoning environ-ments and as the recipient of the Robert Engelmore award from the Association for the Advancement of Artificial Intelligence (AAAI) for leadership in Semantic Web research and in bridging Artificial Intel-ligence (AI) and eScience, significant contributions to deployed AI applications, and extensive service to the AI community. Deborah leads a number of large diverse data intensive resource efforts and her team is creating next-generation ontology-enabled research infrastructure for work in large interdisciplinary settings. Prior to joining RPI, Deborah was the acting director of the Knowledge Systems, Artificial Intelligence Laboratory, and Senior Research Scientist in the Computer Science Department of Stanford University, and previous to that she was at AT&T Bell Laboratories. Deborah consults with numerous large corporations as well as emerging startup companies wishing to plan, develop, deploy, and maintain Semantic Web and/or AI applications. Some areas of recent work include: data science, next-generation health advisors, ontology design and evolution environments, semantically enabled virtual observatories, semantic integration of scientific data, context-aware mobile applications, search, eCommerce, configuration, and supply chain management. Deborah holds a Bachelor of Math and Computer Science from Duke University, a Master of Computer Science from University of California at Berkeley, and a Ph.D. in Computer Science from Rutgers University.


Target Audience:

The book is for students and academicians of ontology engineering/computer science.


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