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Ontology Engineering
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, manipulat...
Knowledge Graphs
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 ...
Models in Software Engineering
This book constitutes the thoroughly refereed post-workshop proceedings of 10 internationl workshops and 2 symposia held as satellite events of the 10th International Conference on Model Driven Engineering Languages and Systems, MoDELS 2007, in Nashville, TN, USA, in September/October 2007 (see LNCS 4735). The 29 revised full papers were carefully selected for inclusion in the book and are presented along with a doctoral and an educators' symposium section. The papers are organized in topical sections representing the various workshops: aspect-oriented modeling (AOM 2007), language engineering (ATEM2007), model driven development of advanced user interfaces (MDDAUI 2007), model size metrics (MSM 2007), model-based design of trustworthy health information systems (MOTHIS 2007), model-driven engineering, verification and validation (MoDeVVa 2007), modelling systems with OCL (Ocl4All 2007), Models@run.time, multi-paradigm modeling: concepts and tools (MPM 2007), quality in modeling, doctoral symposium, and educators' symposium.
Linked Data Visualization
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...
The Semantic Web - ISWC 2006
This book constitutes the refereed proceedings of the 5th International Semantic Web Conference, ISWC 2006, held in Athens, GA, USA in November 2006. It features more than 52 papers that address all current issues in the field of the semantic Web, ranging from theoretical aspects to various applied topics. An additional 14 papers detail applications in government, public health, public service, academic, and industry.
Designing and Building Enterprise Knowledge Graphs
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.
Ontologies
This book describes the state-of-the-art in ontology-driven information systems (ODIS) and gives a complete perspective on the problems, solutions and open research questions in this field. The book covers four broad areas: foundations of ODIS, ontological engineering, ODIS architectures, and ODIS applications. It will trigger innovative thought processes and open up significant new domains in ODIS research.
Semantic Web Enabled Software Engineering
Over the last decade, ontology has become an important modeling component in software engineering. Semantic Web Enabled Software Engineering presents some critical findings on opening a new direction of the research of Software Engineering, by exploiting Semantic Web technologies. Most of these findings are from selected papers from the Semantic Web Enabled Software Engineering (SWESE) series of workshops starting from 2005. Edited by two leading researchers, this advanced text presents a unifying and contemporary perspective on the field. The book integrates in one volume a unified perspective on concepts and theories of connecting Software Engineering and Semantic Web. It presents state-of-the-art techniques on how to use Semantic Web technologies in Software Engineering and introduces techniques on how to design ontologies for Software Engineering.
Handbook on Ontologies
An ontology is a formal description of concepts and relationships that can exist for a community of human and/or machine agents. The notion of ontologies is crucial 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 considering ontology languages, ontology engineering methods, example ontologies, infrastructures and technologies for ontologies, and how to bring this all into ontology-based infrastructures and applications that are among the best of their kind. The field of ontologies has tremendously developed and grown in the five years since the first edition of the "Handbook on Ontologies". Therefore, its revision includes 21 completely new chapters as well as a major re-working of 15 chapters transferred to this second edition.
Semantic Web and Model-Driven Engineering
The next enterprise computing era will rely on the synergy between both technologies: semantic web and model-driven software development (MDSD). The semantic web organizes system knowledge in conceptual domains according to its meaning. It addresses various enterprise computing needs by identifying, abstracting and rationalizing commonalities, and checking for inconsistencies across system specifications. On the other side, model-driven software development is closing the gap among business requirements, designs and executables by using domain-specific languages with custom-built syntax and semantics. It focuses on using modeling languages as programming languages. Among many areas of applic...
