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This book is a printed edition of the Special Issue "Scalable Interactive Visualization" that was published in Informatics
Book Synopsis Scalable Interactive Visualization by : Achim Ebert
Download or read book Scalable Interactive Visualization written by Achim Ebert and published by MDPI. This book was released on 2018-05-08 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Scalable Interactive Visualization" that was published in Informatics
Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser
Book Synopsis Interactive Data Visualization for the Web by : Scott Murray
Download or read book Interactive Data Visualization for the Web written by Scott Murray and published by "O'Reilly Media, Inc.". This book was released on 2013-03-11 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser
Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth
Book Synopsis Big Data by : James Warren
Download or read book Big Data written by James Warren and published by Simon and Schuster. This book was released on 2015-04-29 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Table of Contents A new paradigm for Big Data PART 1 BATCH LAYER Data model for Big Data Data model for Big Data: Illustration Data storage on the batch layer Data storage on the batch layer: Illustration Batch layer Batch layer: Illustration An example batch layer: Architecture and algorithms An example batch layer: Implementation PART 2 SERVING LAYER Serving layer Serving layer: Illustration PART 3 SPEED LAYER Realtime views Realtime views: Illustration Queuing and stream processing Queuing and stream processing: Illustration Micro-batch stream processing Micro-batch stream processing: Illustration Lambda Architecture in depth
Book Synopsis Focused Multidimensional Scaling by : Lea M. Urpa
Download or read book Focused Multidimensional Scaling written by Lea M. Urpa and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
While computers can help us manage data, human judgment and domain expertise is what turns it into understanding. Meeting the challenges of increasingly large and complex data requires methods that richly integrate the capabilities of both people and machines. In response to these challenges, this thesis contributes new languages and models for visualization design that power interactive systems for scalable data analysis. In these languages, users can be imprecise about low-level design decisions as the system leverages this ambiguity to optimize the visual design and necessary computation. Vega-Lite is a high-level declarative language for rapidly creating interactive visualizations, while also providing a convenient yet powerful representation for tools that generate visualizations. Vega-Lite uses smart defaults to fill in low-level details to create effective designs. The declarative design facilitates optimization of the required data processing. Draco is a model of visualization design that extends Vega-Lite with shareable design guidelines, formal reasoning over the design space, and visualization recommendation. We show how we can use Draco to construct increasingly sophisticated automated visualization design and recommendation systems, including systems based on weights learned directly from the results of graphical perception experiments. We take a user-centric perspective on systems for scalable exploratory analysis. Considering both the backend and frontend concerns, we present Falcon, an interactive crossfilter application where users can interact with billions of records without latencies that negatively affect their exploration. To scale beyond billions of records, we present Pangloss, a visual analysis system that uses approximate query processing but provides eventual guarantees using Optimistic Visualization. In this concept, we treat approximate query processing as a user experience problem to address users' primary concern: trust in their exploration results. Falcon and Pangloss contribute techniques for scalable interaction and exploration of large data volumes by making principled trade-offs among people's latency tolerance, precomputation, and the level of approximation.
Book Synopsis Interactive Systems for Scalable Visualization and Analysis by : Dominik Moritz
Download or read book Interactive Systems for Scalable Visualization and Analysis written by Dominik Moritz and published by . This book was released on 2019 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: While computers can help us manage data, human judgment and domain expertise is what turns it into understanding. Meeting the challenges of increasingly large and complex data requires methods that richly integrate the capabilities of both people and machines. In response to these challenges, this thesis contributes new languages and models for visualization design that power interactive systems for scalable data analysis. In these languages, users can be imprecise about low-level design decisions as the system leverages this ambiguity to optimize the visual design and necessary computation. Vega-Lite is a high-level declarative language for rapidly creating interactive visualizations, while also providing a convenient yet powerful representation for tools that generate visualizations. Vega-Lite uses smart defaults to fill in low-level details to create effective designs. The declarative design facilitates optimization of the required data processing. Draco is a model of visualization design that extends Vega-Lite with shareable design guidelines, formal reasoning over the design space, and visualization recommendation. We show how we can use Draco to construct increasingly sophisticated automated visualization design and recommendation systems, including systems based on weights learned directly from the results of graphical perception experiments. We take a user-centric perspective on systems for scalable exploratory analysis. Considering both the backend and frontend concerns, we present Falcon, an interactive crossfilter application where users can interact with billions of records without latencies that negatively affect their exploration. To scale beyond billions of records, we present Pangloss, a visual analysis system that uses approximate query processing but provides eventual guarantees using Optimistic Visualization. In this concept, we treat approximate query processing as a user experience problem to address users' primary concern: trust in their exploration results. Falcon and Pangloss contribute techniques for scalable interaction and exploration of large data volumes by making principled trade-offs among people's latency tolerance, precomputation, and the level of approximation.
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Book Synopsis Designing Data-Intensive Applications by : Martin Kleppmann
Download or read book Designing Data-Intensive Applications written by Martin Kleppmann and published by "O'Reilly Media, Inc.". This book was released on 2017-03-16 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization. • Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation, • Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets, • Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications, • Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms. Scientific Visualization will be useful to practitioners of scientific visualization, students interested in both overview and advanced topics, and those interested in knowing more about the visualization process.
Book Synopsis Scientific Visualization by : Charles D. Hansen
Download or read book Scientific Visualization written by Charles D. Hansen and published by Springer. This book was released on 2014-09-18 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization. • Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation, • Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets, • Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications, • Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms. Scientific Visualization will be useful to practitioners of scientific visualization, students interested in both overview and advanced topics, and those interested in knowing more about the visualization process.
Modern database management systems (DBMS) have been designed to efficiently store, manage and perform computations on massive amounts of data. In contrast, many existing visualization systems do not scale seamlessly from small data sets to enormous ones. We have designed a three-tiered visualization system called ScalaR to deal with this issue. ScalaR dynamically performs resolution reduction when the expected result of a DBMS query is too large to be effectively rendered on existing screen real estate. Instead of running the original query, ScalaR inserts aggregation, sampling or filtering operations to reduce the size of the result. This thesis presents the design and implementation of ScalaR, and shows results for two example applications, visualizing earthquake records and satellite imagery data, stored in SciDB as the back-end DBMS.
Book Synopsis Interactive Visualization of Big Data Leveraging Databases for Scalable Computation by : Leilani Marie Battle
Download or read book Interactive Visualization of Big Data Leveraging Databases for Scalable Computation written by Leilani Marie Battle and published by . This book was released on 2013 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern database management systems (DBMS) have been designed to efficiently store, manage and perform computations on massive amounts of data. In contrast, many existing visualization systems do not scale seamlessly from small data sets to enormous ones. We have designed a three-tiered visualization system called ScalaR to deal with this issue. ScalaR dynamically performs resolution reduction when the expected result of a DBMS query is too large to be effectively rendered on existing screen real estate. Instead of running the original query, ScalaR inserts aggregation, sampling or filtering operations to reduce the size of the result. This thesis presents the design and implementation of ScalaR, and shows results for two example applications, visualizing earthquake records and satellite imagery data, stored in SciDB as the back-end DBMS.
Practical data design tips from a data visualization expert of the modern age Data doesn't decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn't it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships. Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator Contains numerous examples and descriptions of patterns and outliers and explains how to show them Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.
Book Synopsis Visualize This by : Nathan Yau
Download or read book Visualize This written by Nathan Yau and published by John Wiley & Sons. This book was released on 2011-06-13 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical data design tips from a data visualization expert of the modern age Data doesn't decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn't it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships. Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator Contains numerous examples and descriptions of patterns and outliers and explains how to show them Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.
A comprehensive discussion of the findings of the PICASSO initiative on ICT policy ICT Policy, Research, and Innovation: Perspectives and Prospects for EU-US Collaboration provides a clearly readable overview of selected information and communication technology (ICT) and policy topics. Rather than deluge the reader with technical details, the distinguished authors provide just enough technical background to make sense of the underlying policy discussions. The book covers policy, research, and innovation topics on technologies as wide-ranging as: Internet of Things Cyber physical systems 5G Big data ICT Policy, Research, and Innovation compares and contrasts the policy approaches taken by the EU and the US in a variety of areas. The potential for future cooperation is outlined as well. Later chapters provide policy perspectives about some major issues affecting EU/US development cooperation, while the book closes with a discussion of how the development of these new technologies is changing our conceptions of fundamental aspects of society.
Book Synopsis ICT Policy, Research, and Innovation by : Svetlana Klessova
Download or read book ICT Policy, Research, and Innovation written by Svetlana Klessova and published by John Wiley & Sons. This book was released on 2020-11-02 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive discussion of the findings of the PICASSO initiative on ICT policy ICT Policy, Research, and Innovation: Perspectives and Prospects for EU-US Collaboration provides a clearly readable overview of selected information and communication technology (ICT) and policy topics. Rather than deluge the reader with technical details, the distinguished authors provide just enough technical background to make sense of the underlying policy discussions. The book covers policy, research, and innovation topics on technologies as wide-ranging as: Internet of Things Cyber physical systems 5G Big data ICT Policy, Research, and Innovation compares and contrasts the policy approaches taken by the EU and the US in a variety of areas. The potential for future cooperation is outlined as well. Later chapters provide policy perspectives about some major issues affecting EU/US development cooperation, while the book closes with a discussion of how the development of these new technologies is changing our conceptions of fundamental aspects of society.
