The Epistemology of Intelligent Semantic Web Systems
The Epistemology of Intelligent Semantic Web Systems

Author: Mathieu d'Aquin

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 78

ISBN-13: 3031794710

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The Semantic Web is a young discipline, even if only in comparison to other areas of computer science. Nonetheless, it already exhibits an interesting history and evolution. This book is a reflection on this evolution, aiming to take a snapshot of where we are at this specific point in time, and also showing what might be the focus of future research. This book provides both a conceptual and practical view of this evolution, especially targeted at readers who are starting research in this area and as support material for their supervisors. From a conceptual point of view, it highlights and discusses key questions that have animated the research community: what does it mean to be a Semantic Web system and how is it different from other types of systems, such as knowledge systems or web-based information systems? From a more practical point of view, the core of the book introduces a simple conceptual framework which characterizes Intelligent Semantic Web Systems. We describe this framework, the components it includes, and give pointers to some of the approaches and technologies that might be used to implement them. We also look in detail at concrete systems falling under the category of Intelligent Semantic Web Systems, according to the proposed framework, allowing us to compare them, analyze their strengths and weaknesses, and identify the key fundamental challenges still open for researchers to tackle.

Natural Language Processing for the Semantic Web
Natural Language Processing for the Semantic Web

Author: Diana Maynard

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 182

ISBN-13: 3031794745

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This book introduces core natural language processing (NLP) technologies to non-experts in an easily accessible way, as a series of building blocks that lead the user to understand key technologies, why they are required, and how to integrate them into Semantic Web applications. Natural language processing and Semantic Web technologies have different, but complementary roles in data management. Combining these two technologies enables structured and unstructured data to merge seamlessly. Semantic Web technologies aim to convert unstructured data to meaningful representations, which benefit enormously from the use of NLP technologies, thereby enabling applications such as connecting text to Linked Open Data, connecting texts to each other, semantic searching, information visualization, and modeling of user behavior in online networks. The first half of this book describes the basic NLP processing tools: tokenization, part-of-speech tagging, and morphological analysis, in addition to the main tools required for an information extraction system (named entity recognition and relation extraction) which build on these components. The second half of the book explains how Semantic Web and NLP technologies can enhance each other, for example via semantic annotation, ontology linking, and population. These chapters also discuss sentiment analysis, a key component in making sense of textual data, and the difficulties of performing NLP on social media, as well as some proposed solutions. The book finishes by investigating some applications of these tools, focusing on semantic search and visualization, modeling user behavior, and an outlook on the future.

Life Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision
Life Cycle Analysis and Assessment in Civil Engineering: Towards an Integrated Vision

Author: Robby Caspeele

Publisher: CRC Press

Published: 2018-10-15

Total Pages: 5111

ISBN-13: 1351857568

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This volume contains the papers presented at IALCCE2018, the Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE2018), held in Ghent, Belgium, October 28-31, 2018. It consists of a book of extended abstracts and a USB device with full papers including the Fazlur R. Khan lecture, 8 keynote lectures, and 390 technical papers from all over the world. Contributions relate to design, inspection, assessment, maintenance or optimization in the framework of life-cycle analysis of civil engineering structures and infrastructure systems. Life-cycle aspects that are developed and discussed range from structural safety and durability to sustainability, serviceability, robustness and resilience. Applications relate to buildings, bridges and viaducts, highways and runways, tunnels and underground structures, off-shore and marine structures, dams and hydraulic structures, prefabricated design, infrastructure systems, etc. During the IALCCE2018 conference a particular focus is put on the cross-fertilization between different sub-areas of expertise and the development of an overall vision for life-cycle analysis in civil engineering. The aim of the editors is to provide a valuable source of cutting edge information for anyone interested in life-cycle analysis and assessment in civil engineering, including researchers, practising engineers, consultants, contractors, decision makers and representatives from local authorities.

Demystifying OWL for the Enterprise
Demystifying OWL for the Enterprise

Author: Michael Uschold

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 237

ISBN-13: 3031794826

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After a slow incubation period of nearly 15 years, a large and growing number of organizations now have one or more projects using the Semantic Web stack of technologies. The Web Ontology Language (OWL) is an essential ingredient in this stack, and the need for ontologists is increasing faster than the number and variety of available resources for learning OWL. This is especially true for the primary target audience for this book: modelers who want to build OWL ontologies for practical use in enterprise and government settings. The purpose of this book is to speed up the process of learning and mastering OWL. To that end, the focus is on the 30% of OWL that gets used 90% of the time. Others who may benefit from this book include technically oriented managers, semantic technology developers, undergraduate and post-graduate students, and finally, instructors looking for new ways to explain OWL. The book unfolds in a spiral manner, starting with the core ideas. Each subsequent cycle reinforces and expands on what has been learned in prior cycles and introduces new related ideas. Part 1 is a cook's tour of ontology and OWL, giving an informal overview of what things need to be said to build an ontology, followed by a detailed look at how to say them in OWL. This is illustrated using a healthcare example. Part 1 concludes with an explanation of some foundational ideas about meaning and semantics to prepare the reader for subsequent chapters. Part 2 goes into depth on properties and classes, which are the core of OWL. There are detailed descriptions of the main constructs that you are likely to need in every day modeling, including what inferences are sanctioned. Each is illustrated with real-world examples. Part 3 explains and illustrates how to put OWL into practice, using examples in healthcare, collateral, and financial transactions. A small ontology is described for each, along with some key inferences. Key limitations of OWL are identified, along with possible workarounds. The final chapter gives a variety of practical tips and guidelines to send the reader on their way.

Ontology Engineering
Ontology Engineering

Author: Elisa Kendall

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 102

ISBN-13: 3031794869

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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 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.

Web Data APIs for Knowledge Graphs
Web Data APIs for Knowledge Graphs

Author: Albert Meroño-Peñuela

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 92

ISBN-13: 3031019172

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This book describes a set of methods, architectures, and tools to extend the data pipeline at the disposal of developers when they need to publish and consume data from Knowledge Graphs (graph-structured knowledge bases that describe the entities and relations within a domain in a semantically meaningful way) using SPARQL, Web APIs, and JSON. To do so, it focuses on the paradigmatic cases of two middleware software packages, grlc and SPARQL Transformer, which automatically build and run SPARQL-based REST APIs and allow the specification of JSON schema results, respectively. The authors highlight the underlying principles behind these technologies—query management, declarative languages, new levels of indirection, abstraction layers, and separation of concerns—, explain their practical usage, and describe their penetration in research projects and industry. The book, therefore, serves a double purpose: to provide a sound and technical description of tools and methods at the disposal of publishers and developers to quickly deploy and consume Web Data APIs on top of Knowledge Graphs; and to propose an extensible and heterogeneous Knowledge Graph access infrastructure that accommodates a growing ecosystem of querying paradigms.

Validating RDF Data
Validating RDF Data

Author: Jose Emilio Labra Gayo

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 304

ISBN-13: 3031794788

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RDF and Linked Data have broad applicability across many fields, from aircraft manufacturing to zoology. Requirements for detecting bad data differ across communities, fields, and tasks, but nearly all involve some form of data validation. This book introduces data validation and describes its practical use in day-to-day data exchange. The Semantic Web offers a bold, new take on how to organize, distribute, index, and share data. Using Web addresses (URIs) as identifiers for data elements enables the construction of distributed databases on a global scale. Like the Web, the Semantic Web is heralded as an information revolution, and also like the Web, it is encumbered by data quality issues. The quality of Semantic Web data is compromised by the lack of resources for data curation, for maintenance, and for developing globally applicable data models. At the enterprise scale, these problems have conventional solutions. Master data management provides an enterprise-wide vocabulary, while constraint languages capture and enforce data structures. Filling a need long recognized by Semantic Web users, shapes languages provide models and vocabularies for expressing such structural constraints. This book describes two technologies for RDF validation: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL), the rationales for their designs, a comparison of the two, and some example applications.

Linked Data Visualization
Linked Data Visualization

Author: Laura Po

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 143

ISBN-13: 3031794907

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Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains. The development of Linked Data Visualization techniques and tools has been followed as the primary means for the analysis of this vast amount of information by data scientists, domain experts, business users, and citizens. This book covers a wide spectrum of visualization issues, providing an overview of the recent advances in this area, focusing on techniques, tools, and use cases of visualization and visual analysis of LD. It presents the basic concepts related to data visualization and the LD technologies, the techniques employed for data visualization based on the characteristics of data techniques for Big Data visualization, use tools and use cases in the LD context, and finally a thorough assessment of the usability of these tools under different scenarios. The purpose of this book is to offer a complete guide to the evolution of LD visualization for interested readers from any background and to empower them to get started with the visual analysis of such data. This book can serve as a course textbook or a primer for all those interested in LD and data visualization.

Designing and Building Enterprise Knowledge Graphs
Designing and Building Enterprise Knowledge Graphs

Author: Juan Sequeda

Publisher: Springer Nature

Published: 2022-05-31

Total Pages: 142

ISBN-13: 3031019164

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This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice.\ It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies. Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge. In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers.