You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
This book explores the connection between digital fabrication and the design build studio in both academic and professional studios. The book presents 17 essays and cases studies from well-known scholars and practitioners, including Kengo Kuma, Joseph Choma, Dan Rockhill, Keith Zawistowski, and Marie Zawistowski, whose theoretical and practical work addresses design build at various levels. Four introductory essays trace the history of the design build movement, exploring the emergence of design build in the pedagogy of the Bauhaus, the integration of technology into architectural design, and the influence of the act of making on the design build studio. The rest of the book is divided into ...
This Festschrift volume, published in honor of John Mylopoulos on the occasion of his retirement from the University of Toronto, contains 25 high-quality papers, written by leading scientists in the field of conceptual modeling. The volume has been divided into six sections. The first section focuses on the foundations of conceptual modeling and contains material on ontologies and knowledge representation. The four sections on software and requirements engineering, information systems, information integration, and web and services, represent the chief current application domains of conceptual modeling. Finally, the section on implementations concentrates on projects that build tools to support conceptual modeling. With its in-depth coverage of diverse topics, this book could be a useful companion to a course on conceptual modeling.
What value does semantic data modeling offer? As an information architect or data science professional, let’s say you have an abundance of the right data and the technology to extract business gold—but you still fail. The reason? Bad data semantics. In this practical and comprehensive field guide, author Panos Alexopoulos takes you on an eye-opening journey through semantic data modeling as applied in the real world. You’ll learn how to master this craft to increase the usability and value of your data and applications. You’ll also explore the pitfalls to avoid and dilemmas to overcome for building high-quality and valuable semantic representations of data. Understand the fundamental...
Knowledge graphs are increasingly used in scientific and industrial applications. The large number and size of knowledge graphs published as Linked Data in autonomous sources has led to the development of various interfaces to query these knowledge graphs. Therefore, effective query processing approaches that enable efficient information retrieval from these knowledge graphs need to address the capabilities and limitations of different Linked Data Fragment interfaces. This book investigates novel approaches to addressing the challenges that arise in the presence of decentralized, heterogeneous sources of knowledge graphs. The effectiveness of these approaches is empirically evaluated and dem...
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 ...
Integrates a platform-driven decision framework with the model-driven architecture (MDA). This practical guide explains how to combine three technology areas - MDA, ontologies, and software product lines - in order to integrate several platform-specific software products into a single MDA
The complex information systems which have evolved in recent decades rely on robust and coherent representations in order to function. Such representations and associated reasoning techniques constitute the modern discipline of formal ontology, which is now applied to fields such as artificial intelligence, computational linguistics, bioinformatics, GIS, conceptual modeling, knowledge engineering, information retrieval, and the semantic web. Ontologies are increasingly employed in a number of complex real-world application domains. For instance, in biology and medicine, more and more principle-based ontologies are being developed for the description of biological and biomedical phenomena. To...
Researchers in areas such as artificial intelligence, formal and computational linguistics, biomedical informatics, conceptual modeling, knowledge engineering and information retrieval have come to realize that a solid foundation for their research calls for serious work in ontology, understood as a general theory of the types of entities and relations that make up their respective domains of inquiry. In all these areas, attention is now being focused on the content of information rather than on just the formats and languages used to represent information. The clearest example of this development is provided by the many initiatives growing up around the project of the Semantic Web. And, as t...
An ontology is a description (like a formal specification of a program) of concepts and relationships that can exist for an agent or a community of agents. The concept is important for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies. The handbook demonstrates standards that have been created recently, it surveys methods that have been developed and it shows how to bring both into practice of ontology infrastructures and applications that are the best of their kind.