Data Visualization Techniques

Download or read book Data Visualization Techniques written by Chandrajit Bajaj and published by . This book was released on 1999 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data visualization techniques are a means to manipulate sampled and computed data for comprehensive display. Visualized data can be static or in motion, to provide visual explanations of algorithms or general information. This book draws on examples from a broad selection of subject areas, such as atmospheric sciences or biology, which deal with diverse data analysis and visualization techniques. The various visualization methodologies covered in this book also include moving images as well as static. It is an important source of information for computer graphics software engineers, graduates and researchers who work in the field of visualization techniques. Unique features in this book include: Details of data visualization techniques for scalar, vector and tensor field data and accompanying data structures Explanation of how to express visual images in computational terms and turn these into display, with minimum delay Methodology for "probing" a displayed visualization, in order to elicit more detail Collection of information from several interrelated subject areas in one volume Trends in Software - edited by Balachander Krishnamurthy of AT&T Research - is a sister publication of the journal Software: Practice and Experience

Download or read book Interactive Data Visualization written by Matthew O. Ward and published by CRC Press. This book was released on 2015-06-11 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Updated Guide to the Visualization of Data for Designers, Users, and ResearchersInteractive Data Visualization: Foundations, Techniques, and Applications, Second Edition provides all the theory, details, and tools necessary to build visualizations and systems involving the visualization of data. In color throughout, it explains basic terminology

Download or read book Linked Data Visualization written by Laura Po and published by Morgan & Claypool Publishers. This book was released on 2020-03-20 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 adopted as the established practice 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 topics, 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 core concepts related to data visualization and LD technologies, techniques employed for data visualization based on the characteristics of data, techniques for Big Data visualization, 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 as a primer for all those interested in LD and data visualization.

Download or read book Now You See it written by Stephen Few and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Teaches simple, fundamental, and practical techniques that anyone can use to make sense of numbers." - cover.

Download or read book Security Data Visualization written by Greg Conti and published by No Starch Press. This book was released on 2007 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a range of cyber security issues explains how to utilize graphical approaches to displaying and understanding computer security data, such as network traffic, server logs, and executable files, offering guidelines for identifying a network attack, how to assess a system for vulnerabilities with Afterglow and RUMINT visualization software, and how to protect a system from additional attacks. Original. (Intermediate)

Download or read book Data Visualization written by S. Margret Anouncia and published by Springer Nature. This book was released on 2020-03-03 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the recent trends and developments in the fields of information processing and information visualization. In view of the increasing amount of data, there is a need to develop visualization techniques to make that data easily understandable. Presenting such approaches from various disciplines, this book serves as a useful resource for graduates.

Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results