Overview
- In-depth coverage of biomedical ontologies
- Practical, theory-based methodology for ontology quality assurance
- Rigorous algorithms with visualized real-world examples
Part of the book series: Synthesis Lectures on Data, Semantics, and Knowledge (SLDSK)
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Table of contents (8 chapters)
Keywords
About this book
The book synthesizes research on the analysis of biomedical ontologies using formal concept analysis, including through auditing, curation, and enhancement. As the evolution of biomedical ontologies almost inevitably involves manual work, formal methods are a particularly useful tool for ontological engineering and practice, particularly in uncovering unexpected "bugs" and content materials.
The book first introduces simple but formalized strategies for discovering undesired and incoherent patterns in ontologies before exploring the application of formal concept analysis for semantic completeness. The book then turns to formal concept analysis, a classical approach used in the mathematical treatment of orders and lattices, as an ontological engineering principle, focusing on the structural property of ontologies with respect to its conformation to lattice or not (non-lattice). The book helpfully covers the development of more efficient algorithms for non-latticedetection and extraction required by exhaustive lattice/non-lattice analysis. The book goes on to highlight the power and utility of uncovering non-lattice structure for debugging ontologies and describes methods that leverage the linguistic information in concept names (labels) for ontological analysis. It also addresses visualization and performance evaluation issues before closing with an overview and forward-looking perspectives on the field.This book is intended for graduate students and researchers interested in biomedical ontologies and their applications. It can be a useful supplement for courses on knowledge representation and engineering and also provide readers with a reference for related scientific publications and literature to assist in identifying potential research topics. All mathematical concepts and notations used in this book can be found in standard discrete mathematics textbooks, and the appendix at the end of the book provides a list of key ontological resources, as well as annotated non-lattice and lattice examples that were discovered using the authors' methods, demonstrating how "bugs are fixed" by converting non-lattices to lattices with minimal edit changes.
Authors and Affiliations
About the authors
Licong Cui received her Ph.D. in Computer Science from Case Western Reserve University. She is an assistant professor in School of Biomedical Informatics at the University of Texas Health Science Center at Houston. Before joining UTHealth, she was an assistant professor in the Department of Computer Science and member of the Institute for Biomedical Informatics at the University of Kentucky. Her research interests include ontologies and terminologies, neuroinformatics, big data analytics, large-scale data integration and management, and information extraction and retrieval. She has been a Principal Investigatorof several highly competitive research awards funded by the NIH and the NSF. She is a recipient of the prestigious NSF CAREER Award.
Rashmie Abeysinghe received his B.S. in Computer Science from University of Peradeniya, Peradeniya, Sri Lanka and Ph.D. in Computer Science from University of Kentucky. He completed a Summer Internship at the National Library of Medicine, NIH. After completing his Ph.D. study, he joined the Department of Neurology, McGovern Medical School at the University of Texas Health Science Center at Houston as a Research Scientist. His research interests revolve around biomedical ontologies particularly from a quality assurance perspective, information extraction, and deep learning. His paper won a Distinguished Paper Award at the 2021 American Medical Informatics Association (AMIA) Annual Symposium. His papers were also selected as finalists for both the 2018 and 2019 AMIA Annual Symposium Student Paper Competitions.
Bibliographic Information
Book Title: Formal Methods for the Analysis of Biomedical Ontologies
Authors: Guo-Qiang Zhang, Rashmie Abeysinghe, Licong Cui
Series Title: Synthesis Lectures on Data, Semantics, and Knowledge
DOI: https://doi.org/10.1007/978-3-031-12131-9
Publisher: Springer Cham
eBook Packages: Synthesis Collection of Technology (R0), eBColl Synthesis Collection 11
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-031-12130-2Published: 09 November 2022
Softcover ISBN: 978-3-031-12133-3Published: 10 November 2023
eBook ISBN: 978-3-031-12131-9Published: 08 November 2022
Series ISSN: 2691-2023
Series E-ISSN: 2691-2031
Edition Number: 1
Number of Pages: XIV, 245
Number of Illustrations: 67 b/w illustrations, 52 illustrations in colour
Topics: Data Storage Representation, Data Structures and Information Theory, Artificial Intelligence, Biomedicine, general, Ontology