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Author: Mathieu d'Aquin
Publisher: Springer Nature
ISBN: 3031794710
Category : Mathematics
Languages : en
Pages : 78
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Book Description
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.
Author: Mathieu d'Aquin
Publisher: Springer Nature
ISBN: 3031794710
Category : Mathematics
Languages : en
Pages : 78
Get Book Here
Book Description
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.
Author: Mathieu d'Aquin
Publisher: Morgan & Claypool Publishers
ISBN: 1627050000
Category : Computers
Languages : en
Pages : 90
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Book Description
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.
Author: Michael Uschold
Publisher: Springer Nature
ISBN: 3031794826
Category : Mathematics
Languages : en
Pages : 237
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Book Description
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.
Author: Albert Meroño-Peñuela
Publisher: Springer Nature
ISBN: 3031019172
Category : Computers
Languages : en
Pages : 92
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Book Description
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.
Author: Jose Emilio Labra Gayo
Publisher: Springer Nature
ISBN: 3031794788
Category : Mathematics
Languages : en
Pages : 304
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Book Description
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.
Author: Laura Po
Publisher: Springer Nature
ISBN: 3031794907
Category : Mathematics
Languages : en
Pages : 143
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Book Description
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.
Author: Juan Sequeda
Publisher: Springer Nature
ISBN: 3031019164
Category : Computers
Languages : en
Pages : 142
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Book Description
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.
Author: Aidan Hogan
Publisher: Springer Nature
ISBN: 3031019180
Category : Computers
Languages : en
Pages : 247
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Book Description
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.
Author: Peter Mika
Publisher: Springer Science & Business Media
ISBN: 0387710019
Category : Computers
Languages : en
Pages : 237
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Book Description
Social Networks and the Semantic Web offers valuable information to practitioners developing social-semantic software for the Web. It provides two major case studies. The first case study shows the possibilities of tracking a research community over the Web. It reveals how social network mining from the web plays an important role for obtaining large scale, dynamic network data beyond the possibilities of survey methods. The second case study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies.
Author: Lytras, Miltiadis D.
Publisher: IGI Global
ISBN: 1522571876
Category : Computers
Languages : en
Pages : 415
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Book Description
Continual advancements in web technology have highlighted the need for formatted systems that computers can utilize to easily read and sift through the hundreds of thousands of data points across the internet. Therefore, having the most relevant data in the least amount of time to optimize the productivity of users becomes a priority. Semantic Web Science and Real-World Applications provides emerging research exploring the theoretical and practical aspects of semantic web science and real-world applications within the area of big data. Featuring coverage on a broad range of topics such as artificial intelligence, social media monitoring, and microblogging recommendation systems, this book is ideally designed for IT consultants, academics, professionals, and researchers of web science seeking the current developments, requirements and standards, and technology spaces presented across academia and industries.
