Innovative Approaches Of Data Visualization And Visual Analytics
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📒Innovative Approaches Of Data Visualization And Visual Analytics ✍ Huang, Mao Lin
✏Innovative Approaches of Data Visualization and Visual Analytics Book Summary : 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.
✏User Centered Design of Visual Analytics and Its Applications in Healthcare Book Summary : In the era of big data, healthcare practitioners are increasingly generating and analyzing data. The huge volume of data provides opportunities for evidence based medicine to answer research and practical questions, and for individuals to make better informed, smarter decision. Yet, making sense of massive healthcare datasets remains a fundamental challenge. In order to make inferences on the data, an effective visual representations of the data is needed. We propose visualization as a means to derive inferences on healthcare data. Design of visual analytics tools, therefore, becomes important in the healthcare domain. Healthcare is a broad area involving users with high variation in roles, expertise, and background. The diverse characteristics of users and their shifting contexts makes it a challenge to process and to present healthcare data in appropriate visual representations that is directly relevant to the analytics tasks.We advocate using the User-Centered Design (UCD) approach in designing and developing visual analytics tools in healthcare. The core research question is how a user centered approach should be adopted in designing visual analytics tools. We address the question by bringing the user centered design process and visual analytics process together, and by applying interdisciplinary methods, such as data mining, information visualization and network analytics. In particular, the dissertation looks to three studies in the healthcare domain where practitioners follow UCD to design visual analytics in healthcare domain. We emphasis the role of user involvement in the entire iterative design lifecycle. The users spanning these studies include patients, physicians, nanomaterial scientists, biomedical professionals, and healthcare policy makers. The three studies are:1. Developing a visual web-based tool called VisOSA to interpret and explore medical records of patients with sleep apnea. For physicians, the ClinicView provides an interactive tool to have an overview of the entire medical record of patients including anomalies, and therefore help with generating research hypothesis. For patients, the PatientView allows the lay individual - without any medical background - to understand their health conditions under treatment at a glance. We also defined medical dashboard in this study. We conducted a supporting quantitative behavioral research to examine the effect of multiple monitors on people's performance. Results suggested that the medical dashboard needs to be arranged as that the most important information is in a single screen. 2. Studying the nanomaterial environmental impact (NEI) is a critical task in nano-health and safety. The information visualization module for NEIMiner is a visual analytic tool that can efficiently query and present large-scale bibliography meta-data, NEI characterizations and nanomaterial toxicity. It supports nanomaterial scientists and analysts to explore the concepts and relationships in studying nanomaterial toxicity and its impact on health. 3. Translating research findings into effective clinical care is another overwhelming task. VATS is a scalable multi-scale visual analytical tool for advancing translational sciences. The system integrates the data of National Center for Advancing Translational Science (NCATS) funded projects and publications from NIH Research Portfolio Online Reporting Tools (RePORTER) and PubMed, and helps healthcare policy makers to understand the big picture of translational science and to evaluate the impact of NCATS funded projects through publicly available data sources.Through these studies, we discuss how innovative visual analytics techniques and capabilities with help users understand and act on various type of data. The results and applications demonstrate what purposes visualizations are used for each problem, how the design and development team make decisions around datasets, and the different visual representations healthcare practitioners use to explore and gain insight of data. The research contributions are (1) a joint model of UCD and visual analytics process that overcomes the design challenges, (2) a justification of how existing data mining and visualization techniques can be usefully combined to support analytics task in healthcare, (3) the approaches to integrate and enrich the dataset, and turn the data into reliable and provable information, (4) the visual encoding and interaction mechanisms to present complex information, (5) three visual analytics system built are beneficial to healthcare community and society. The design guidelines and recommendations generated from these studies are applicable to various domains. We hope this work inspire more innovations and conversations at the intersection of user centered design and visual analytics.
📒Big Data Concepts Methodologies Tools And Applications ✍ Management Association, Information Resources
✏Big Data Concepts Methodologies Tools and Applications Book Summary : The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.
📒Business Intelligence Concepts Methodologies Tools And Applications ✍ Management Association, Information Resources
✏Business Intelligence Concepts Methodologies Tools and Applications Book Summary : Data analysis is an important part of modern business administration, as efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Business Intelligence: Concepts, Methodologies, Tools, and Applications presents a comprehensive examination of business data analytics along with case studies and practical applications for businesses in a variety of fields and corporate arenas. Focusing on topics and issues such as critical success factors, technology adaptation, agile development approaches, fuzzy logic tools, and best practices in business process management, this multivolume reference is of particular use to business analysts, investors, corporate managers, and entrepreneurs in a variety of prominent industries.
📒Technological Advancements And The Impact Of Actor Network Theory ✍ Tatnall, Arthur
✏Technological Advancements and the Impact of Actor Network Theory Book Summary : Actor-Network Theory (ANT) has existed as a topic of interest among social theorists for decades. Due to the prevalence of technology in modern society, discussions over the influence of actor-network theory on the changing scope of technology can assist in facilitating further research and scientific thought. Technological Advancements and the Impact of Actor-Network Theory focuses on cross-disciplinary research as well as examples of the use of actor-network theory in a variety of fields, including medicine, education, business, engineering, environmental science, computer science, and social science. This timely publication is well-suited for reference use by academicians, researchers, upper-level students, and theorists.
📒The Visual Imperative ✍ Lindy Ryan
✏The Visual Imperative Book Summary : Data is powerful. It separates leaders from laggards and it drives business disruption, transformation, and reinvention. Today’s most progressive companies are using the power of data to propel their industries into new areas of innovation, specialization, and optimization. The horsepower of new tools and technologies have provided more opportunities than ever to harness, integrate, and interact with massive amounts of disparate data for business insights and value – something that will only continue in the era of the Internet of Things. And, as a new breed of tech-savvy and digitally native knowledge workers rise to the ranks of data scientist and visual analyst, the needs and demands of the people working with data are changing, too. The world of data is changing fast. And, it’s becoming more visual. Visual insights are becoming increasingly dominant in information management, and with the reinvigorated role of data visualization, this imperative is a driving force to creating a visual culture of data discovery. The traditional standards of data visualizations are making way for richer, more robust and more advanced visualizations and new ways of seeing and interacting with data. However, while data visualization is a critical tool to exploring and understanding bigger and more diverse and dynamic data, by understanding and embracing our human hardwiring for visual communication and storytelling and properly incorporating key design principles and evolving best practices, we take the next step forward to transform data visualizations from tools into unique visual information assets. Discusses several years of in-depth industry research and presents vendor tools, approaches, and methodologies in discovery, visualization, and visual analytics Provides practicable and use case-based experience from advisory work with Fortune 100 and 500 companies across multiple verticals Presents the next-generation of visual discovery, data storytelling, and the Five Steps to Data Storytelling with Visualization Explains the Convergence of Visual Analytics and Visual discovery, including how to use tools such as R in statistical and analytic modeling Covers emerging technologies such as streaming visualization in the IOT (Internet of Things) and streaming animation
📒Data Visualization ✍ Andy Kirk
✏Data Visualization Book Summary : A comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process. This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data. There is no skill, no knowledge and no role-based pre-requisites or expectations of anyone reading this book.
📒Visualizing With Text ✍ Richard Brath
✏Visualizing with Text Book Summary : Visualizing with Text uncovers the rich palette of text elements usable in visualizations from simple labels through to documents. Using a multidisciplinary research effort spanning across fields including visualization, typography, and cartography, it builds a solid foundation for the design space of text in visualization. The book illustrates many new kinds of visualizations, including microtext lines, skim formatting, and typographic sets that solve some of the shortcomings of well-known visualization techniques. Key features: More than 240 illustrations to aid inspiration of new visualizations Eight new approaches to data visualization leveraging text Quick reference guide for visualization with text Builds a solid foundation extending current visualization theory Bridges between visualization, typography, text analytics, and natural language processing Designers, developers, and academics can use this book as a reference and inspiration for new approaches to visualization in any application that uses text.
📒Visual Data Mining ✍ Simeon Simoff
✏Visual Data Mining Book Summary : Visual Data Mining—Opening the Black Box Knowledge discovery holds the promise of insight into large, otherwise opaque datasets. Thenatureofwhatmakesaruleinterestingtoauserhasbeendiscussed 1 widely but most agree that it is a subjective quality based on the practical u- fulness of the information. Being subjective, the user needs to provide feedback to the system and, as is the case for all systems, the sooner the feedback is given the quicker it can in?uence the behavior of the system. There have been some impressive research activities over the past few years but the question to be asked is why is visual data mining only now being - vestigated commercially? Certainly, there have been arguments for visual data 2 mining for a number of years – Ankerst and others argued in 2002 that current (autonomous and opaque) analysis techniques are ine?cient, as they fail to - rectly embed the user in dataset exploration and that a better solution involves the user and algorithm being more tightly coupled. Grinstein stated that the “current state of the art data mining tools are automated, but the perfect data mining tool is interactive and highly participatory,” while Han has suggested that the “data selection and viewing of mining results should be fully inter- tive, the mining process should be more interactive than the current state of the 2 art and embedded applications should be fairly automated . ” A good survey on 3 techniques until 2003 was published by de Oliveira and Levkowitz .
📒Good Charts ✍ Scott Berinato
✏Good Charts Book Summary : Dataviz—the new language of business A good visualization can communicate the nature and potential impact of information and ideas more powerfully than any other form of communication. For a long time “dataviz” was left to specialists—data scientists and professional designers. No longer. A new generation of tools and massive amounts of available data make it easy for anyone to create visualizations that communicate ideas far more effectively than generic spreadsheet charts ever could. What’s more, building good charts is quickly becoming a need-to-have skill for managers. If you’re not doing it, other managers are, and they’re getting noticed for it and getting credit for contributing to your company’s success. In Good Charts, dataviz maven Scott Berinato provides an essential guide to how visualization works and how to use this new language to impress and persuade. Dataviz today is where spreadsheets and word processors were in the early 1980s—on the cusp of changing how we work. Berinato lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping. This book is much more than a set of static rules for making visualizations. It taps into both well-established and cutting-edge research in visual perception and neuroscience, as well as the emerging field of visualization science, to explore why good charts (and bad ones) create “feelings behind our eyes.” Along the way, Berinato also includes many engaging vignettes of dataviz pros, illustrating the ideas in practice. Good Charts will help you turn plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas.