Exploring the Collective Unconscious in the Age of Digital Media by
Exploring the Collective Unconscious in a Digital Age investigates the cognitive significance of an altered mediated reality that appears to have all the dimensions of a dreamscape. This book presents the idea that if the digital media-sphere proves to be structurally and functionally analogous to a dreamscape, the Collective Unconscious researched by Carl Jung and the Cognitive Unconscious researched by George Lakoff are susceptible to research according to the parameters of hard science. This pivotal research-based publication is ideally designed for use by psychologists, theorists, researchers, and graduate-level students studying human cognition and the influence of the digital media revolution.
Imagined Landscapes by
Imagined Landscapes teams geocritical analysis with digital visualization techniques to map and interrogate films, novels, and plays in which space and place figure prominently. Drawing upon A Cultural Atlas of Australia, a database-driven interactive digital map that can be used to identify patterns of representation in Australia's cultural landscape, the book presents an integrated perspective on the translation of space across narrative forms and pioneers new ways of seeing and understanding landscape. It offers fresh insights on cultural topography and spatial history by examining the technical and conceptual challenges of georeferencing fictional and fictionalized places in narratives. Among the items discussed are Wake in Fright, a novel by Kenneth Cook, adapted iconically to the screen and recently onto the stage; the Australian North as a mythic space; spatial and temporal narrative shifts in retellings of the story of Alexander Pearce, a convict who gained notoriety for resorting to cannibalism after escaping from a remote Tasmanian penal colony; travel narratives and road movies set in Western Australia; and the challenges and spatial politics of mapping spaces for which there are no coordinates.
Thinking Like Einstein by
Albert Einstein once said that all of his most important and productive thinking was done by playing with images in his imagination. Only in a secondary stage did he translate — with great effort, he says — these images into the language of words and mathematics that could be understood by others. According to Thomas G. West, Einstein was a classic example of a strong visual thinker, a person who tends to think in images and visual patterns, and sometimes has difficulty with words and numbers. In his awarding-winning book, In the Mind’s Eye, West discussed the connections between highly talented, visually oriented persons like Einstein and certain learning disabilities such as dyslexia. Now, in Thinking Like Einstein, West investigates the new worlds of visual thinking, insight, and creativity made possible by computer graphics and information visualization technologies. He argues that, with the rapid spread of inexpensive and powerful computers, we are now at the beginning of a major transition, moving from an old world based mainly on words and numbers to a new world where high level work in all fields will eventually involve insights based on the display and manipulation of complex information using moving computer images. West profiles several highly creative visual thinkers, such as James Clerk Maxwell, Nikola Tesla, and Richard Feynman, pointing out that there is a long history of using visualization rather than words or numbers to solve problems. Citing the longstanding historical conflicts between image lovers and image haters, West examines the relationship of art, scientific knowledge, and differences in brain capabilities - observing how modern visual thinkers with visualization technologies seem to have learned how to cut through the problems of overspecialization in academia and in the workplace. West predicts that computer visualization technology will radically change the way we all work and think. For thousands of years the technology of writing and reading has tended to promote the dominance of the left hemisphere of the brain, with its linear processing of words and numbers. Now the spread of graphical computer technologies is permitting a return to our visual roots with a new balance between hemispheres and ways of thinking - presenting new opportunities for problem solving and big picture thinking. Thus, he argues that the newest technologies will help us to reaffirm some of our oldest capabilities, allowing us to see previously unseen patterns and to restore a balance in thought and action.
Graphical Data Analysis with R by
See How Graphics Reveal Information Graphical Data Analysis with Rshows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages and the R code is available at rosuda.org/GDA. Graphical data analysis is useful for data cleaning, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting local patterns, evaluating modelling output, and presenting results. This book guides you in choosing graphics and understanding what information you can glean from them. It can be used as a primary text in a graphical data analysis course or as a supplement in a statistics course. Colour graphics are used throughout.
Applied time series analysis by
Virtually any random process developing chronologically can be viewed as a time series. In economics, closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis includes examples across a variety of fields, develops theory, and provides software to address time series problems in a broad spectrum of fields. The authors organize the information in such a format that graduate students in applied science, statistics, and economics can satisfactorily navigate their way through the book while maintaining mathematical rigor.
One of the unique features of Applied Time Series Analysis is the associated software, GW-WINKS, designed to help students easily generate realizations from models and explore the associated model and data characteristics. The text explores many important new methodologies that have developed in time series, such as ARCH and GARCH processes, time varying frequencies (TVF), wavelets, and more. Other programs (some written in R and some requiring S-plus) are available on an associated website for performing computations related to the material in the final four chapters.
Bodies in Code: Interfaces with Digital Media by
Bodies in Code explores how our bodies experience and adapt to digital environments. Cyberculture theorists have tended to overlook biological reality when talking about virtual reality, and Mark B. N. Hansen's book shows what they've been missing. Cyberspace is anchored in the body, he argues, and it's the body--not high-tech computer graphics--that allows a person to feel like they are really "moving" through virtual reality. Of course these virtual experiences are also profoundly affecting our very understanding of what it means to live as embodied beings. Hansen draws upon recent work in visual culture, cognitive science, and new media studies, as well as examples of computer graphics, websites, and new media art, to show how our bodies are in some ways already becoming virtual.
Digital Prohibition: Piracy and Authorship in New Media Art by
The act of creation requires us to remix existing cultural content and yet recent sweeping changes to copyright laws have criminalized the creative act as a violation of corporate rights in a commodified world. Copyright was originally designed to protect publishers, not authors, and has now gained a stranglehold on our ability to transport, read, write, teach and publish digital materials. Contrasting Western models with issues of piracy as practiced in Asia, Digital Prohibition explores the concept of authorship as a capitalist institution and posits the Marxist idea of the multitude (à la Antonio Negri and Michael Hardt, and Paulo Virno) as a new collaborative model for creation in the digital age. Looking at how digital culture has transformed unitary authorship from its book-bound parameters into a collective and dispersed endeavor, Dr. Guertin examines process-based forms as diverse as blogs, Facebook, Twitter, performance art, immersive environments, smart mobs, hacktivism, tactical media, machinima, generative computer games (like Spore and The Sims) and augmented reality.
Handbook of Statistical Graphics using SAS ODS by
Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full graphics capabilities of SAS, A Handbook of Statistical Graphics Using SAS ODS covers essential graphical methods needed in every statistician’s toolkit. It explains how to implement the methods using SAS 9.4.
The handbook shows how to use SAS to create many types of statistical graphics for exploring data and diagnosing fitted models. It uses SAS’s newer ODS graphics throughout as this system offers a number of advantages, including ease of use, high quality of results, consistent appearance, and convenient semiautomatic graphs from the statistical procedures.
Each chapter deals graphically with several sets of example data from a wide variety of areas, such as epidemiology, medicine, and psychology. These examples illustrate the use of graphic displays to give an overview of data, to suggest possible hypotheses for testing new data, and to interpret fitted statistical models. The SAS programs and data sets are available online.
Introducing Data Science by
Summary Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started. About the Book Introducing Data ScienceIntroducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You’ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You’ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. What’s Inside Handling large data Introduction to machine learning Using Python to work with data Writing data science algorithms About the Reader This book assumes you're comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required. About the Authors Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors. Table of Contents Data science in a big data world The data science process Machine learning Handling large data on a single computer First steps in big data Join the NoSQL movement The rise of graph databases Text mining and text analytics Data visualization to the end user
An Introduction to R for Quantitative Economics by
This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free, extremely flexible and extensible. The book addresses the specific needs of economists, and helps them move up the R learning curve. It covers some mathematical topics such as, graphing the Cobb-Douglas function, using R to study the Solow growth model, in addition to statistical topics, from drawing statistical graphs to doing linear and logistic regression. It uses data that can be downloaded from the internet, and which is also available in different R packages. With some treatment of basic econometrics, the book discusses quantitative economics broadly and simply, looking at models in the light of data. Students of economics or economists keen to learn how to use R would find this book very useful.
Locative Media by
Not only is locative media one of the fastest growing areas in digital technology, but questions of location and location-awareness are increasingly central to our contemporary engagements with online and mobile media, and indeed media and culture generally. This volume is a comprehensive account of the various location-based technologies, services, applications, and cultures, as media, with an aim to identify, inventory, explore, and critique their cultural, economic, political, social, and policy dimensions internationally. In particular, the collection is organized around the perception that the growth of locative media gives rise to a number of crucial questions concerning the areas of culture, economy, and policy.
New Companion to Digital Humanities by
This highly-anticipated volume has been extensively revised to reflect changes in technology, digital humanities methods and practices, and institutional culture surrounding the valuation and publication of digital scholarship. A fully revised edition of a celebrated reference work, offering the most comprehensive and up-to-date collection of research currently available in this rapidly evolving discipline Includes new articles addressing topical and provocative issues and ideas such as retro computing, desktop fabrication, gender dynamics, and globalization Brings together a global team of authors who are pioneers of innovative research in the digital humanities Accessibly structured into five sections exploring infrastructures, creation, analysis, dissemination, and the future of digital humanities Surveys the past, present, and future of the field, offering essential research for anyone interested in better understanding the theory, methods, and application of the digital humanities
Perspectives on Data Science for Software Engineering by
Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community's leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains
Practical Graph Mining with R by
Discover Novel and Insightful Knowledge from Data Represented as a Graph Practical Graph Mining with Rpresents a "do-it-yourself" approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or clusters of nodes that share common patterns of attributes and relationships, the extraction of patterns that distinguish one category of graphs from another, and the use of those patterns to predict the category of new graphs. Hands-On Application of Graph Data Mining Each chapter in the book focuses on a graph mining task, such as link analysis, cluster analysis, and classification. Through applications using real data sets, the book demonstrates how computational techniques can help solve real-world problems. The applications covered include network intrusion detection, tumor cell diagnostics, face recognition, predictive toxicology, mining metabolic and protein-protein interaction networks, and community detection in social networks. Develops Intuition through Easy-to-Follow Examples and Rigorous Mathematical Foundations Every algorithm and example is accompanied with R code. This allows readers to see how the algorithmic techniques correspond to the process of graph data analysis and to use the graph mining techniques in practice. The text also gives a rigorous, formal explanation of the underlying mathematics of each technique. Makes Graph Mining Accessible to Various Levels of Expertise Assuming no prior knowledge of mathematics or data mining, this self-contained book is accessible to students, researchers, and practitioners of graph data mining. It is suitable as a primary textbook for graph mining or as a supplement to a standard data mining course. It can also be used as a reference for researchers in computer, information, and computational science as well as a handy guide for data analytics practitioners.
SAS programming and data visualization techniques by
SAS Programming and Data Visualization Techniques: A Power User’s Guide brings together a wealth of ideas about strategic and tactical solutions to everyday situations experienced when transferring, extracting, processing, analyzing, and reporting the valuable data you have at your fingertips. Best, you can achieve most of the solutions using the SAS components you already license, meaning that this book’s insights can keep you from throwing money at problems needlessly.
Author Philip R. Holland advises a broad range of clients throughout Europe and the United States as an independent consultant and founder of Holland Numerics Ltd, a SAS technical consultancy. In this book he explains techniques―through code samples and example―that will enable you to increase your knowledge of all aspects of SAS programming, improve your coding productivity, and interface SAS with other programs.
He also provides an expert’s overview of Graph Templates, which was recently moved into Base SAS. You will learn to create attractive, standardized, reusable, and platform-independent graphs―both statistical and non-statistical―to help you and your business users explore, visualize, and capitalize on your company’s data. In addition, you will find many examples and cases pertaining to healthcare, finance, retail, and other industries.
Tableau Your Data! : Fast and Easy Visual Analysis with Tableau Software by
Transform your organization's data into actionable insights with Tableau Tableau is designed specifically to provide fast and easy visual analytics. The intuitive drag-and-drop interface helps you create interactive reports, dashboards, and visualizations, all without any special or advanced training. This all new edition of Tableau Your Data! is your Tableau companion, helping you get the most out of this invaluable business toolset. Tableau Your Data! shows you how to build dynamic, best of breed visualizations using the Tableau Software toolset. This comprehensive guide covers the core feature set for data analytics, and provides clear step-by-step guidance toward best practices and advanced techniques that go way beyond the user manual. You'll learn how Tableau is different from traditional business information analysis tools, and how to navigate your way around the Tableau 9.0 desktop before delving into functions and calculations, as well as sharing with the Tableau Server. Analyze data more effectively with Tableau Desktop Customize Tableau's settings for your organization's needs with detailed real-world examples on data security, scaling, syntax, and more Deploy visualizations to consumers throughout the enterprise - from sales to marketing, operations to finance, and beyond Understand Tableau functions and calculations and leverage Tableau across every link in the value chain Learn from actual working models of the book's visualizations and other web-based resources via a companion website Tableau helps you unlock the stories within the numbers, and Tableau Your Data! puts the software's full functionality right at your fingertips.
Visualizing Financial Data by
A fresh take on financial data visualization for greater accuracy and understanding Your data provides a snapshot of the state of your business and is key to the success of your conversations, decisions, and communications. But all of that communication is lost -- or incorrectly interpreted -- without proper data visualizations that provide context and accurate representation of the numbers. In Visualizing Financial Data, authors Julie Rodriguez and Piotr Kaczmarek draw upon their understanding of information design and visual communication to show you how to turn your raw data into meaningful information. Coverage includes current conventions paired with innovative visualizations that cater to the unique requirements across financial domains, including investment management, financial accounting, regulatory reporting, sales, and marketing communications. Presented as a series of case studies, this highly visual guide presents problems and solutions in the context of real-world scenarios. With over 250 visualizations, you'll have access to relevant examples that serve as a starting point to your implementations. * Expand the boundaries of data visualization conventions and learn new approaches to traditional charts and graphs * Optimize data communications that cater to you and your audience * Provide clarity to maximize understanding * Solve data presentation problems using efficient visualization techniques * Use the provided companion website to follow along with examples The companion website gives you the illustration files and the source data sets, and points you to the types of resources you need to get started.
