When you looking for computers visualization and history, you must consider not only the quality but also price and customer reviews. But among hundreds of product with different price range, choosing suitable computers visualization and history is not an easy task. In this post, we show you how to find the right computers visualization and history along with our top-rated reviews. Please check out our suggestions to find the best computers visualization and history for you.
Best computers visualization and history
1. Design for Information: An Introduction to the Histories, Theories, and Best Practices Behind Effective Information Visualizations
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Used Book in Good ConditionDescription
2. Computers, Visualization, and History: How New Technology Will Transform Our Understanding of the Past
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This visionary and thoroughly accessible book examines how digital environments and virtual reality have altered the ways historians think and communicate ideas and how the new language of visualization transforms our understanding of the past. Drawing on familiar graphic models--maps, flow charts, museum displays, films--the author shows how images can often convey ideas and information more efficiently and accurately than words. With emerging digital technology, these images will become more sophisticated, manipulable, and multidimensional, and provide historians with new tools and environments to construct historical narratives. Moving beyond the traditional book based on linear narrative, digital scholarship based on visualization and hypertext will offer multiple perspectives, dimensions, and experiences that transform the ways historians work and people imagine and learn about history.
This second edition of Computers, Visualization, and History features expanded coverage of such topics as sequential narratives, 3-D modeling, simulation, and video games, as well as our theoretical understanding of space and immersive experience. The author has also added "Guidelines for Visual Composition in History" for history and social studies teachers who wish to use technology for student assignments. Also new to the second edition is a web link feature that users of the digital edition can use to enhance visualization within the text.
3. Computers, Visualization and History: How New Technology Will Transform Our Understanding of the Past (History, Humanities, and New Technology)
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Used Book in Good ConditionDescription
For hundreds of years historians have used prose and narrative to convey history. This is about to change, thanks to new technology, digital scholarship, and computerized "visualization." Text itself has inherent limitations: The very use of words - their meaning and the connections among them - shapes and restricts how historians think and communicate ideas. The rise of the computer is radically altering how human beings receive and process information. Digital environments and virtual reality are adding a third dimension to communication and creating a new visual language. This visionary and thoroughly accessible book examines this entire revolutionary phenomenon and how historians will utilize the new medium of computers and the new language of visualization to transform our understanding of history. Drawing on familiar graphic models - maps, flow charts, museum displays, and films - the author shows how images can often convey ideas and information more efficiently and accurately than words. With emerging digital technology, these images will become more sophisticated, manipulable, and multidimensional, and provide historians with new tools and environments to construct historical narratives. Just as the transition from prehistoric cave paintings to the spread of literacy changed how people think and process information, so has - and will - the computer. Moving beyond the traditional book based on linear narrative, digital scholarship based on visualization and hypertext will offer multiple perspectives, dimensions, and experiences that will transform how historians work and how people imagine and learn about history.4. Exploring Big Historical Data: The Historian's Macroscope
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The Digital Humanities have arrived at a moment when digital Big Data is becoming more readily available, opening exciting new avenues of inquiry but also new challenges. This pioneering book describes and demonstrates the ways these data can be explored to construct cultural heritage knowledge, for research and in teaching and learning. It helps humanities scholars to grasp Big Data in order to do their work, whether that means understanding the underlying algorithms at work in search engines, or designing and using their own tools to process large amounts of information.
Demonstrating what digital tools have to offer and also what 'digital' does to how we understand the past, the authors introduce the many different tools and developing approaches in Big Data for historical and humanistic scholarship, show how to use them, what to be wary of, and discuss the kinds of questions and new perspectives this new macroscopic perspective opens up. Authored 'live' online with ongoing feedback from the wider digital history community, Exploring Big Historical Data breaks new ground and sets the direction for the conversation into the future. It represents the current state-of-the-art thinking in the field and exemplifies the way that digital work can enhance public engagement in the humanities.
Exploring Big Historical Data should be the go-to resource for undergraduate and graduate students confronted by a vast corpus of data, and researchers encountering these methods for the first time. It will also offer a helping hand to the interested individual seeking to make sense of genealogical data or digitized newspapers, and even the local historical society who are trying to see the value in digitizing their holdings.
5. White Heat Cold Logic: British Computer Art 19601980 (Leonardo)
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The history of a pioneering era in computer-based art too often neglected by postwar art histories and institutions.
Technological optimism, even utopianism, was widespread at midcentury; in Britain, Harold Wilson in 1963 promised a new nation forged from the white heat of the technological revolution. In this heady atmosphere, pioneering artists transformed the cold logic of computing into a new medium for their art, and played a central role in connecting technology and culture. White Heat Cold Logic tells the story of these early British digital and computer artistsand fills in a missing chapter in contemporary art history.
In this heroic period of computer art, artists were required to build their own machines, collaborate closely with computer scientists, and learn difficult computer languages. White Heat Cold Logic's chapters, many written by computer art pioneers themselves, describe the influence of cybernetics, with its emphasis on process and interactivity; the connections to the constructivist movement; and the importance of work done in such different venues as commercial animation, fine art schools, and polytechnics.
The advent of personal computing and graphical user interfaces in 1980 signaled the end of an era, and today we do not have so many dreams of technological utopia. And yet our highly technologized and mediated world owes much to these early practitioners, especially for expanding our sense of what we can do with new technologies.
Contributors
Roy Ascott, Stephen Bell, Paul Brown, Stephen Bury, Harold Cohen, Ernest Edmonds, Mara Fernndez, Simon Ford, John Hamilton Frazer, Jeremy Gardiner, Charlie Gere, Adrian Glew, Beryl Graham, Stan Hayward, Grisham Howard, Richard Ihnatowicz, Nicholas Lambert, Malcolm Le Grice, Tony Longson, Brent MacGregor, George Mallen, Catherine Mason, Jasia Reichardt, Stephen A. R. Scrivener, Brian Reffin Smith, Alan Sutcliffe, Doron D. Swade, John Vince, Richard Wright, Aleksandar Zivanovic
6. Visualize This: The FlowingData Guide to Design, Visualization, and Statistics
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John Wiley SonsDescription
Practical data design tips from a data visualization expert of the modern ageData 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.
From the Author: Telling Stories with Data
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Visualization and data design all come easier with practice, and you can advance your skills with every new dataset and project. To begin though, you need a proper foundation and know what tools are available to you (but not let them bog you down). I wrote Visualize This with that in mind.
You'll be exposed to a variety of software and code and jump right into real-world datasets so that you can learn visualization by doing, and most importantly be able to apply what you learn to your own data.
Three Data Visualization Steps:
1) Ask a Question
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When you get a dataset, it sometimes is a challenge figuring out where to start, especially when it's a large dataset. Approach your data with a simple curiosity or a question that you want answered, and go from there.
2) Explore Your Data
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A simple curiosity often leads to more questions, which are a good guide for what stories to dig into. What variables are related to each other? Can you see changes over time? Are there any features in the data that stand out? Find out all you can about your data, because the more you know what's behind the numbers, the better story you can tell.
3) Visualize Your Data
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Once you know the important parts of your data, you can design graphics the best way you see fit. Use shapes, colors, and sizes that make sense and help tell your story clearly to readers. While the base of your charts and graphs will share many of the same properties bars, slices, dots, and lines the final design elements will and should vary by your unique dataset.
7. Big Data in History (Palgrave Pivot)
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Big Data in History introduces the project to create a world-historical archive, tracing the last four centuries of historical dynamics and change. Chapters address the archive's overall plan, how to interpret the past through a global archive, the missions of gathering records, linking local data into global patterns, and exploring the results.8. Mapping Scientific Frontiers: The Quest for Knowledge Visualization
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This is an examination of the history and the state of the art of the quest for visualizing scientific knowledge and the dynamics of its development. Through an interdisciplinary perspective this book presents profound visions, pivotal advances, and insightful contributions made by generations of researchers and professionals, which portrays a holistic view of the underlying principles and mechanisms of the development of science.
This updated and extended second edition:
- highlights the latest advances in mapping scientific frontiers
- examines the foundations of strategies, principles, and design patterns
- provides an integrated and holistic account of major developments across disciplinary boundaries
Anyone who tries to follow the exponential growth of the literature on citation analysis and scientometrics knows how difficult it is to keep pace. Chaomei Chen has identified the significant methods and applications in visual graphics and made them clear to the uninitiated. Derek Price would have loved this book which not only pays homage to him but also to the key players in information science and a wide variety of others in the sociology and history of science.
Eugene Garfield
This is a wide ranging book on information visualization, with a specific focus on science mapping. Science mapping is still in its infancy and many intellectual challenges remain to be investigated and many of which are outlined in the final chapter. In this new edition Chaomei Chen has provided an essential text, useful both as a primer for new entrants and as a comprehensive overview of recent developments for the seasoned practitioner.
Henry Small
Chaomei Chen is a Professor in the College of Information Science and Technology at Drexel University, Philadelphia, USA, and a ChangJiang Scholar at Dalian University of Technology, Dalian, China. He is the Editor-in-Chief of Information Visualization and the author of Turning Points: The Nature of Creativity (Springer, 2012) and Information Visualization: Beyond the Horizon (Springer, 2004, 2006).
9. Malware Data Science: Attack Detection and Attribution
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Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization.Security has become a "big data" problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you'll need to know how to think like a data scientist.
In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualization, and shows you how to apply these methods to malware detection and analysis.
You'll learn how to:
- Analyze malware using static analysis
- Observe malware behavior using dynamic analysis
- Identify adversary groups through shared code analysis
- Catch 0-day vulnerabilities by building your own machine learning detector
- Measure malware detector accuracy
- Identify malware campaigns, trends, and relationships through data visualization
Whether you're a malware analyst looking to add skills to your existing arsenal, or a data scientist interested in attack detection and threat intelligence, Malware Data Science will help you stay ahead of the curve.
