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Designing and Building Enterprise Knowledge Graphs

Author: Juan Sequeda

Publisher: Springer

Published: 2021-08-04

Total Pages: 142

ISBN-13: 9783031007880

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.

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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Knowledge Graphs

Author: Aidan Hogan

Publisher: Morgan & Claypool Publishers

Published: 2021-11-08

Total Pages: 257

ISBN-13: 1636392369

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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.

The Knowledge Graph CookBook

Author: Andreas Blumauer

Publisher:

Published: 2020

Total Pages:

ISBN-13: 9783902796707

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Graph-based Knowledge Representation

Author: Michel Chein

Publisher: Springer Science & Business Media

Published: 2008-10-20

Total Pages: 428

ISBN-13: 1848002866

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This book provides a de?nition and study of a knowledge representation and r- soning formalism stemming from conceptual graphs, while focusing on the com- tational properties of this formalism. Knowledge can be symbolically represented in many ways. The knowledge representation and reasoning formalism presented here is a graph formalism – knowledge is represented by labeled graphs, in the graph theory sense, and r- soning mechanisms are based on graph operations, with graph homomorphism at the core. This formalism can thus be considered as related to semantic networks. Since their conception, semantic networks have faded out several times, but have always returned to the limelight. They faded mainly due to a lack of formal semantics and the limited reasoning tools proposed. They have, however, always rebounded - cause labeled graphs, schemas and drawings provide an intuitive and easily und- standable support to represent knowledge. This formalism has the visual qualities of any graphic model, and it is logically founded. This is a key feature because logics has been the foundation for knowledge representation and reasoning for millennia. The authors also focus substantially on computational facets of the presented formalism as they are interested in knowledge representation and reasoning formalisms upon which knowledge-based systems can be built to solve real problems. Since object structures are graphs, naturally graph homomorphism is the key underlying notion and, from a computational viewpoint, this moors calculus to combinatorics and to computer science domains in which the algorithmicqualitiesofgraphshavelongbeenstudied,asindatabasesandconstraint networks.

Knowledge Graphs and Big Data Processing

Author: Valentina Janev

Publisher: Springer Nature

Published: 2020-07-15

Total Pages: 212

ISBN-13: 3030531996

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This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.

The Instructional Design Knowledge Base

Author: Rita C. Richey

Publisher: Routledge

Published: 2010-10-18

Total Pages: 240

ISBN-13: 1136895418

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The Instructional Design Knowledge Base: Theory, Research and Practice provides ID professionals and students at all levels with a comprehensive exploration of the theories and research that serve as a foundation for current and emerging ID practice. This book offers both current and classic interpretations of theory from a range of disciplines and approaches. It encompasses general systems, communication, learning, early instructional, media, conditions-based, constructivist design and performance-improvement theories. Features include: rich representations of the ID literature concise theory summaries specific examples of how theory is applied to practice recommendations for future research a glossary of related terms a comprehensive list of references. A perfect resource for instructional design and technology doctoral, masters and educational specialist certificate programs, The Instructional Design Knowledge Base provides students and scholars with a comprehensive background for ID practice and a foundation for future ID thinking.

UML for Developing Knowledge Management Systems

Author: Anthony J. Rhem

Publisher: CRC Press

Published: 2005-11-21

Total Pages: 315

ISBN-13: 1135485534

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UML for Developing Knowledge Management Systems provides knowledge engineers the framework in which to identify types of knowledge and where this knowledge exists in an organization. It also shows ways in which to use a standard recognized notation to capture, or model, knowledge to be used in a knowledge management system (KMS). This volume

Design and Use of Relational Databases in Chemistry

Author: TJ O'Donnell

Publisher: CRC Press

Published: 2008-12-05

Total Pages: 248

ISBN-13: 1420064436

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Optimize Your Chemical DatabaseDesign and Use of Relational Databases in Chemistry helps programmers and users improve their ability to search and manipulate chemical structures and information, especially when using chemical database "cartridges". It illustrates how the organizational, data integrity, and extensibility properties of relational dat

The Semantic Web – ISWC 2019

Author: Chiara Ghidini

Publisher: Springer Nature

Published: 2019-10-17

Total Pages: 754

ISBN-13: 303030793X

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The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community. The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.