Mastering Sparql
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Mastering SPARQL
"Mastering SPARQL: Querying the Semantic Web with RDF" is an essential guide for anyone looking to harness the full potential of Semantic Web technologies. This comprehensive text unravels the complexities of SPARQL, the powerful query language that enables seamless interaction with RDF data. Geared towards both beginners and those with some familiarity in the field, the book offers a structured exploration of RDF and SPARQL, blending foundational knowledge with advanced querying techniques to empower readers in managing and analyzing rich, interconnected datasets. Through carefully curated chapters, readers are taken on an informative journey—from understanding the intricacies of the RDF data model to leveraging SPARQL's sophisticated features for real-world applications. Each section builds methodically on the last, covering everything from the fundamentals of SPARQL syntax to optimizing query performance and integrating SPARQL with other Semantic Web technologies. Written with clarity and precision, "Mastering SPARQL" not only equips readers with the technical skills needed to thrive in the realm of semantic data but also inspires them to apply these insights across diverse disciplines, driving innovation and enhancing data-driven decision-making.
Mastering Structured Data on the Semantic Web
A major limitation of conventional web sites is their unorganized and isolated contents, which is created mainly for human consumption. This limitation can be addressed by organizing and publishing data, using powerful formats that add structure and meaning to the content of web pages and link related data to one another. Computers can "understand" such data better, which can be useful for task automation. The web sites that provide semantics (meaning) to software agents form the Semantic Web, the Artificial Intelligence extension of the World Wide Web. In contrast to the conventional Web (the "Web of Documents"), the Semantic Web includes the "Web of Data", which connects "things" (representing real-world humans and objects) rather than documents meaningless to computers. Mastering Structured Data on the Semantic Web explains the practical aspects and the theory behind the Semantic Web and how structured data, such as HTML5 Microdata and JSON-LD, can be used to improve your site’s performance on next-generation Search Engine Result Pages and be displayed on Google Knowledge Panels. You will learn how to represent arbitrary fields of human knowledge in a machine-interpretable form using the Resource Description Framework (RDF), the cornerstone of the Semantic Web. You will see how to store and manipulate RDF data in purpose-built graph databases such as triplestores and quadstores, that are exploited in Internet marketing, social media, and data mining, in the form of Big Data applications such as the Google Knowledge Graph, Wikidata, or Facebook’s Social Graph. With the constantly increasing user expectations in web services and applications, Semantic Web standards gain more popularity. This book will familiarize you with the leading controlled vocabularies and ontologies and explain how to represent your own concepts. After learning the principles of Linked Data, the five-star deployment scheme, and the Open Data concept, you will be ableto create and interlink five-star Linked Open Data, and merge your RDF graphs to the LOD Cloud. The book also covers the most important tools for generating, storing, extracting, and visualizing RDF data, including, but not limited to, Protégé, TopBraid Composer, Sindice, Apache Marmotta, Callimachus, and Tabulator. You will learn to implement Apache Jena and Sesame in popular IDEs such as Eclipse and NetBeans, and use these APIs for rapid Semantic Web application development. Mastering Structured Data on the Semantic Web demonstrates how to represent and connect structured data to reach a wider audience, encourage data reuse, and provide content that can be automatically processed with full certainty. As a result, your web contents will be integral parts of the next revolution of the Web.
Mastering Redis
Author: Jeremy Nelson
language: en
Publisher: Packt Publishing Ltd
Release Date: 2016-05-31
Take your knowledge of Redis to the next level to build enthralling applications with ease About This Book Detailed explanation on Data structure server with powerful strings, lists, sets, sorted-sets, and hashes Learn to Scale your data with Redis Cluster's distributed setup This is a fast paced practical guide full of screenshots and real work examples to help you get to grips with Redis in no time. Who This Book Is For If you are a software developer with some experience with Redis and would now like to elevate your Redis knowledge and skills even further, then this book is for you. What You Will Learn Choose the right Redis data structure for your problem Understand Redis event-loop and implement your own custom C commands Solve complex workflows with Redis server-side scripting with Lua Configure your Redis instance for optimal memory management Scale your data in a distributed manner with Redis Cluster Improve the stability of your Redis solution using Redis Sentinel Complement your existing database and NoSQL environment with Redis Exploit a wide range of features provided by Redis to become a DevOps expert. In Detail Redis is the most popular, open-source, key value data structure server that provides a wide range of capabilities on which multiple platforms can be be built. Its fast and flexible data structures give your existing applications an edge in the development environment. This book is a practical guide which aims to help you deep dive into the world of Redis data structure to exploit its excellent features. We start our journey by understanding the need of Redis in brief, followed by an explanation of Advanced key management. Next, you will learn about design patterns, best practices for using Redis in DevOps environment and Docker containerization paradigm in detail. After this, you will understand the concept of scaling with Redis cluster and Redis Sentinel , followed by a through explanation of incorporating Redis with NoSQL technologies such as Elasticsearch and MongoDB. At the end of this section, you will be able to develop competent applications using these technologies. You will then explore the message queuing and task management features of Redis and will be able to implement them in your applications. Finally, you will learn how Redis can be used to build real-time data analytic dashboards, for different disparate data streams. Style and approach This is a hands on guide full of easy-to-follow examples, that illustrate important concepts and techniques to solve complex problems with Redis.