Download or read book Visual Analytics for Data Scientists written by Natalia Andrienko and published by Springer Nature. This book was released on 2020-08-30 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents the main principles of visual analytics and describes techniques and approaches that have proven their utility and can be readily reproduced. Special emphasis is placed on various instructive examples of analyses, in which the need for and the use of visualisations are explained in detail. The book begins by introducing the main ideas and concepts of visual analytics and explaining why it should be considered an essential part of data science methodology and practices. It then describes the general principles underlying the visual analytics approaches, including those on appropriate visual representation, the use of interactive techniques, and classes of computational methods. It continues with discussing how to use visualisations for getting aware of data properties that need to be taken into account and for detecting possible data quality issues that may impair the analysis. The second part of the book describes visual analytics methods and workflows, organised by various data types including multidimensional data, data with spatial and temporal components, data describing binary relationships, texts, images and video. For each data type, the specific properties and issues are explained, the relevant analysis tasks are discussed, and appropriate methods and procedures are introduced. The focus here is not on the micro-level details of how the methods work, but on how the methods can be used and how they can be applied to data. The limitations of the methods are also discussed and possible pitfalls are identified. The textbook is intended for students in data science and, more generally, anyone doing or planning to do practical data analysis. It includes numerous examples demonstrating how visual analytics techniques are used and how they can help analysts to understand the properties of data, gain insights into the subject reflected in the data, and build good models that can be trusted. Based on several years of teaching related courses at the City, University of London, the University of Bonn and TU Munich, as well as industry training at the Fraunhofer Institute IAIS and numerous summer schools, the main content is complemented by sample datasets and detailed, illustrated descriptions of exercises to practice applying visual analytics methods and workflows.

Download or read book Visual Analytics for Relationships in Scientific Data written by and published by . This book was released on 2009 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Domain scientists hope to address grand scientific challenges by exploring the abundance of data generated and made available through modern high-throughput techniques. Typical scientific investigations can make use of novel visualization tools that enable dynamic formulation and fine-tuning of hypotheses to aid the process of evaluating sensitivity of key parameters. These general tools should be applicable to many disciplines: allowing biologists to develop an intuitive understanding of the structure of coexpression networks and discover genes that reside in critical positions of biological pathways, intelligence analysts to decompose social networks, and climate scientists to model extrapolate future climate conditions. By using a graph as a universal data representation of correlation, our novel visualization tool employs several techniques that when used in an integrated manner provide innovative analytical capabilities. Our tool integrates techniques such as graph layout, qualitative subgraph extraction through a novel 2D user interface, quantitative subgraph extraction using graph-theoretic algorithms or by querying an optimized B-tree, dynamic level-of-detail graph abstraction, and template-based fuzzy classification using neural networks. We demonstrate our system using real-world workflows from several large-scale studies. Parallel coordinates has proven to be a scalable visualization and navigation framework for multivariate data. However, when data with thousands of variables are at hand, we do not have a comprehensive solution to select the right set of variables and order them to uncover important or potentially insightful patterns. We present algorithms to rank axes based upon the importance of bivariate relationships among the variables and showcase the efficacy of the proposed system by demonstrating autonomous detection of patterns in a modern large-scale dataset of time-varying climate simulation.

Download or read book Mastering the Information Age Solving Problems with Visual Analytics written by Daniel A. Keim and published by Florian Mansmann. This book was released on 2010 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semantic Interaction for Visual Analytics written by Alex Endert and published by Morgan & Claypool Publishers. This book was released on 2016-09-16 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses semantic interaction, a user interaction methodology for visual analytic applications that more closely couples the visual reasoning processes of people with the computation. This methodology affords user interaction on visual data representations that are native to the domain of the data. User interaction in visual analytics systems is critical to enabling visual data exploration. Interaction transforms people from mere viewers to active participants in the process of analyzing and understanding data. This discourse between people and data enables people to understand aspects of their data, such as structure, patterns, trends, outliers, and other properties that ultimately result in insight. Through interacting with visualizations, users engage in sensemaking, a process of developing and understanding relationships within datasets through foraging and synthesis. The book provides a description of the principles of semantic interaction, providing design guidelines for the integration of semantic interaction into visual analytics, examples of existing technologies that leverage semantic interaction, and a discussion of how to evaluate these technologies. Semantic interaction has the potential to increase the effectiveness of visual analytic technologies and opens possibilities for a fundamentally new design space for user interaction in visual analytics systems.

Download or read book Exploratory Analysis of Spatial and Temporal Data written by Natalia Andrienko and published by Springer Science & Business Media. This book was released on 2006-03-28 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploratory data analysis (EDA) is about detecting and describing patterns, trends, and relations in data, motivated by certain purposes of investigation. As something relevant is detected in data, new questions arise, causing specific parts to be viewed in more detail. So EDA has a significant appeal: it involves hypothesis generation rather than mere hypothesis testing. The authors describe in detail and systemize approaches, techniques, and methods for exploring spatial and temporal data in particular. They start by developing a general view of data structures and characteristics and then build on top of this a general task typology, distinguishing between elementary and synoptic tasks. This typology is then applied to the description of existing approaches and technologies, resulting not just in recommendations for choosing methods but in a set of generic procedures for data exploration. Professionals practicing analysis will profit from tested solutions – illustrated in many examples – for reuse in the catalogue of techniques presented. Students and researchers will appreciate the detailed description and classification of exploration techniques, which are not limited to spatial data only. In addition, the general principles and approaches described will be useful for designers of new methods for EDA.

Download or read book Visual Analytics and Interactive Technologies Data Text and Web Mining Applications written by Zhang, Qingyu and published by IGI Global. This book was released on 2010-10-31 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a comprehensive reference on concepts, algorithms, theories, applications, software, and visualization of data mining, text mining, Web mining and computing/supercomputing, covering state-of-the-art of the theory and applications of mining"--

Download or read book Illuminating the Path written by James J. Thomas and published by . This book was released on 2005 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Illuminating the Path is a call to action for researchers and developers to help safeguard our nation by transforming information overload into insights through visual analytics - the science of analytical reasoning facilitated by interactive visual interfaces. Achieving this will require interdisciplinary, collaborative efforts of researchers from throughout academia, industry, and the national laboratories.

Download or read book Eye Tracking and Visual Analytics written by Michael Burch and published by CRC Press. This book was released on 2022-09-01 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visualization and visual analytics are powerful concepts for exploring data from various application domains. The endless number of possible parameters and the many ways to combine visual variables as well as algorithms and interaction techniques create lots of possibilities for building such techniques and tools. The major goal of those tools is to include the human users with their tasks at hand, their hypotheses, and research questions to provide ways to find solutions to their problems or at least to hint them in a certain direction to come closer to a problem solution. However, due to the sheer number of design variations, it is unclear which technique is suitable for those tasks at hand, requiring some kind of user evaluation to figure out how the human users perform while solving their tasks. The technology of eye tracking has existed for a long time; however, it has only recently been applied to visualization and visual analytics as a means to provide insights to the users’ visual attention behavior. This generates another kind of dataset that has a spatio-temporal nature and hence demands for advanced data science and visual analytics concepts to find insights into the recorded eye movement data, either as a post process or even in real-time. This book describes aspects from the interdisciplinary field of visual analytics, but also discusses more general approaches from the field of visualization as well as algorithms and data handling. A major part of the book covers research on those aspects under the light and perspective of eye tracking, building synergy effects between both fields – eye tracking and visual analytics – in both directions, i.e. eye tracking applied to visual analytics and visual analytics applied to eye tracking data. Technical topics discussed in the book include: • Visualization; • Visual Analytics; • User Evaluation; • Eye Tracking; • Eye Tracking Data Analytics; Eye Tracking and Visual Analytics includes more than 500 references from the fields of visualization, visual analytics, user evaluation, eye tracking, and data science, all fields which have their roots in computer science. Eye Tracking and Visual Analytics is written for researchers in both academia and industry, particularly newcomers starting their PhD, but also for PostDocs and professionals with a longer research history in one or more of the covered research fields. Moreover, it can be used to get an overview about one or more of the involved fields and to understand the interface and synergy effects between all of those fields. The book might even be used for teaching lectures in the fields of information visualization, visual analytics, and/or eye tracking.

Download or read book Data Visualization written by Kieran Healy and published by Princeton University Press. This book was released on 2018-12-18 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible primer on how to create effective graphics from data This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides hands-on instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions

Download or read book Visual Analytics in Personalized Health written by Nadya Calderon Romero and published by . This book was released on 2020 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the era of "big data analytics" for healthcare, the personalized medicine promise offers a shift to the provision of care enabled by our technical ability to quantify and assess large volumes of biomedical data. This message however, often seems to strengthen a notion of healthcare from a "biomedical positivism framework", that is, that diagnosis of disease, medical image analysis, integration of devices, and ultimately, the selection of the appropriate therapy is empowered by volumes of data and algorithmic accuracy, thus improving the patient's illness. In this research program, we approached expert biomolecular analysts, recorded their sensemaking process, and analyzed the role of data visualization technologies while they performed analysis of multi-omic data for a direct-to-consumer service of personalized health. We uncovered the nature of the analysts turning to their human-interaction skillset to address the health reality of each consumer they worked for. Assertions about the scientific validity and the amount of data, often emphasize the claims of this personalized health approach, but in practice, the analysts turned to attend goals, preferences, to find actionable evidence in the data, and to frame a relatable health summary story for the clients. The role of technology design in scenarios like this one will be fundamental in properly translating and bridging the effort from these emergent providers (the analysts) in communication with the end consumers. Our findings suggest that both parties benefit from analytic capacities to explore and understand the strength of each piece of evidence in the case, including the evidence that is provided by the clients themselves beyond their biological samples. We believe that this work, along with the research methodologies deployed in work-settings, are a contribution to the Visual Analytics community to support the tasks of bio scientists in personalized medicine, as much as an HCI initiative in support of evidence-based models of preventive healthcare with large amounts of data.

Download or read book Innovative Approaches of Data Visualization and Visual Analytics written by Huang, Mao Lin and published by IGI Global. This book was released on 2013-07-31 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to rapid advances in hardware and software technologies, network infrastructure and data have become increasingly complex, requiring efforts to more effectively comprehend and analyze network topologies and information systems. Innovative Approaches of Data Visualization and Visual Analytics evaluates the latest trends and developments in force-based data visualization techniques, addressing issues in the design, development, evaluation, and application of algorithms and network topologies. This book will assist professionals and researchers working in the fields of data analysis and information science, as well as students in computer science and computer engineering, in developing increasingly effective methods of knowledge creation, management, and preservation.

Download or read book Interactive Visual Data Analysis written by Christian Tominski and published by CRC Press. This book was released on 2020-04-01 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data. The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. Addressing today’s large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis. The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book accessible to a broad interdisciplinary audience from students, to experts in the field, to practitioners in data-intensive application domains. Features: Dedicated to the synthesis of visual, interactive, and analysis methods Systematic top-down view on visualization, interaction, and automatic analysis Broad coverage of fundamental and advanced visualization techniques Comprehensive chapter on interacting with visual representations Extensive integration of automatic computational methods Accessible portrayal of cutting-edge visual analytics technology Foreword by Jack van Wijk For more information, you can also visit the author website, where the book's figures are made available under the CC BY Open Access license.

Download or read book Data Analytics for Intelligent Transportation Systems written by Mashrur Chowdhury and published by Elsevier. This book was released on 2017-04-05 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. - Includes case studies in each chapter that illustrate the application of concepts covered - Presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies - Contains contributors from both leading academic and commercial researchers - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications

Download or read book Research Data Visualization and Scientific Graphics written by MARTINS. ZAUMANIS and published by . This book was released on 2021-07-22 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: Poor data charts and graphics are hindering the effective transfer of knowledge in academia. To get your research noticed and respected, this step-by-step guide will demonstrate essential techniques for creating informative scientific visualizations. By reading this book, you will learn: ✓ Eight bulletproof progressions for turning research data into convincing charts ✓ Eleven graphical features for converting scientific concepts into self-explanatory diagrams and scientific illustrations ✓ Straightforward visualization principles that help to interpret research results The straightforward approaches presented in this book are designed with efficiency in mind. By reviewing a variety of good and bad examples, you will learn how to include scientific visualization in your research communication routine. No artistic talent required. Clear data charts and informative graphics draw citations to papers, make presentations memorable, and encourage reviewers to approve research proposals. This book will show you how to make it happen. What's included: 1) Web resources, including a comparison of different software and online tools for data visualization and scientific illustrations 2) Two printable cheat sheets that summarize the advice from the book 3) A book full of actionable advice for efficiently creating convincing data charts and illuminating scientific graphics About the author My name is Martins Zaumanis and I am obsessed with finding ways to communicate science visually. For example, during the last half a year of my Ph.D., I spent almost every evening hand-drawing my research just so that I could present a memorable TEDx talk. But I don't expect you to become obsessed. Quite the opposite: I developed an approach that will allow you to create great data charts and scientific illustrations without taking away time from what you love most - research

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

Download or read book Expanding the Frontiers of Visual Analytics and Visualization written by John Dill and published by Springer Science & Business Media. This book was released on 2012-04-17 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of computer graphics combines display hardware, software, and interactive techniques in order to display and interact with data generated by applications. Visualization is concerned with exploring data and information graphically in such a way as to gain information from the data and determine significance. Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces. Expanding the Frontiers of Visual Analytics and Visualization provides a review of the state of the art in computer graphics, visualization, and visual analytics by researchers and developers who are closely involved in pioneering the latest advances in the field. It is a unique presentation of multi-disciplinary aspects in visualization and visual analytics, architecture and displays, augmented reality, the use of color, user interfaces and cognitive aspects, and technology transfer. It provides readers with insights into the latest developments in areas such as new displays and new display processors, new collaboration technologies, the role of visual, multimedia, and multimodal user interfaces, visual analysis at extreme scale, and adaptive visualization.

Download or read book Visual Exploration and Comparative Analytics of Multidimensional Data Sets written by Xiaotong Liu and published by . This book was released on 2016 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, rapidly growing amounts of data with numerous attributes and variables arise in various areas of science, engineering, business, and others. Analysis of the multi-faceted information contained in multidimensional data sets has already led to breakthroughs in many fields and emergence of new information-based industries. Data with high dimensionality and complexity has far exceeded our human ability for comprehension without powerful tools. Visualization enhances human's understanding by organizing information in graphical display, offering the possibility of visual exploration of data for knowledge discovery and sense-making. Visual exploration strengthens human perceptual capabilities with visual interfaces to guide data navigation, actively engaging users into the exploration process to make knowledge discovery much more efficient. However, due to the increasing heterogeneity and complexity of multidimensional data, the multidimensional data space exceeds human comprehension. Novel representations are needed to display and organize data items based on the relationships of the dimensions in multidimensional data sets. Furthermore, visual analysis of multidimensional data sets often requires investigating the hidden relationships between different dimensions and specific items to understand the multi-faceted properties of the data sets. The enormous multidimensional data space complicates the search of potentially interesting relations between dimensions and data items. Powerful and versatile visualization tools are thus needed to allow users to analyze and compare complex relations and heterogeneous structures in multidimensional data for knowledge discovery and sense-making. In this dissertation, we investigate critical aspects of multidimensional data visualization and comparative analytics in assisting users in visual exploration of multidimensional data for knowledge discovery and sense-making. Specifically, we address the questions: How can we design multidimensional visualizations to enable effective visual summarization of multi-faceted data characteristics? How can we enhance the power of multidimensional visualizations with comparative analytics to allow visual identification and explanation of complex data relationships? Based on theoretical foundations of visualization and visual analytics, we approach the questions with various research methodologies such as creative design methods, quantitative studies and qualitative studies. This dissertation contributes novel comparative visualization techniques for multidimensional data, novel multidimensional data analysis methods, design implications and guidelines, and generalizable visual exploration frameworks. First, we propose the CorrelatedMultiples visualization that organizes multidimensional data items in 2D display space based on their correlations and similarities in the original high-dimensional space. Second, we investigate the effects of representations and juxtaposition designs on graphical perception of adjacency matrix visualizations, and present the TileMatrix visualization for visualizing a large number of matrices. Third, we describe a novel association analysis method to identify informative and unique scalar values in multivariate scientific data sets, and the visualization framework with multiple interactive views to explore the scalars of interest with confident associations in the multivariate spatial domain. Finally, we present the design study of the SocialBrands tool to assess and analyze public perceptions of brands on social media. This dissertation ends with important reflections on designing comparative visualizations for multidimensional data and discussions of future work.