This text surveys research from the fields of data mining and information visualisation and presents a case for techniques by which information visualisation can be used to uncover real knowledge hidden away in large databases.

The importance of visual data mining, as a strong sub-discipline of data mining, had already been recognized in the beginning of the decade. In 2005 a panel of renowned individuals met to address the shortcomings and drawbacks of the current state of visual information processing. The need for a systematic and methodological development of visual analytics was detected. This book aims at addressing this need. Through a collection of 21 contributions selected from more than 46 submissions, it offers a systematic presentation of the state of the art in the field. The volume is structured in three parts on theory and methodologies, techniques, and tools and applications.

Information visualization is a rapidly growing field that is emerging from research in human-computer interaction, computer science, graphics, visual design, psychology, and business methods. Information visualization is increasingly applied as a critical component in scientific research, digital libraries, data mining, financial data analysis, market studies, manufacturing production control, and drug discovery.

This book is the outcome of the Dagstuhl Seminar on "Information Visualization -- Human-Centered Issues in Visual Representation, Interaction, and Evaluation" held at Dagstuhl Castle, Germany, from May 28 to June 1, 2007. Information Visualization (InfoVis) is a relatively new research area, which focuses on the use of visualization techniques to help people understand and analyze data. This book documents and extends the findings and discussions of the various sessions in detail. The seven contributions cover the most important topics: There are general reflections on the value of information visualization; evaluating information visualizations; theoretical foundations of information visualization; teaching information visualization. And specific aspects on creation and collaboration: engaging new audiences for information visualization; process and pitfalls in writing information visualization research papers; and visual analytics: definition, process, and challenges.

This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual representations, called the General Lines Coordinates (GLCs), is accompanied by a set of algorithms for n-D data classification, clustering, dimension reduction, and Pareto optimization. The mathematical and theoretical analyses and methodology of GLC are included, and the usefulness of this new approach is demonstrated in multiple case studies. These include the Challenger disaster, world hunger data, health monitoring, image processing, text classification, market forecasts for a currency exchange rate, computer-aided medical diagnostics, and others. As such, the book offers a unique resource for students, researchers, and practitioners in the emerging field of Data Science.

Data Mining and Data Visualization focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files. The second section focuses on a variety of statistical methodologies that have proven to be effective in data mining applications. These include clustering, classification, multivariate density estimation, tree-based methods, pattern recognition, outlier detection, genetic algorithms, and dimensionality reduction. The third section focuses on data visualization and covers issues of visualization of high-dimensional data, novel graphical techniques with a focus on human factors, interactive graphics, and data visualization using virtual reality. This book represents a thorough cross section of internationally renowned thinkers who are inventing methods for dealing with a new data paradigm. - Distinguished contributors who are international experts in aspects of data mining - Includes data mining approaches to non-numerical data mining including text data, Internet traffic data, and geographic data - Highly topical discussions reflecting current thinking on contemporary technical issues, e.g. streaming data - Discusses taxonomy of dataset sizes, computational complexity, and scalability usually ignored in most discussions - Thorough discussion of data visualization issues blending statistical, human factors, and computational insights

The fast-paced world created by the accessibility of consumer information through internet-generated data requires improved information-management platforms. The continuous evaluation and evolution of these systems facilitate enhanced data reference and output. Optimizing Data and New Methods for Efficient Knowledge Discovery and Information Resources Management is a critical research publication that provides insight into the varied and rapidly changing fields of knowledge discovery and information resource management. Highlighting a range of topics such as datamining, artificial intelligence, and risk assessment, this book is essential for librarians, academicians, policymakers, information managers, professionals, and researchers in fields that include artificial intelligence, knowledge discovery, data visualization, big data, and information resources management.

Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python. The contributors-all highly experienced with text mining and open-source software-explain how text data are gathered and processed from a w

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.

Introduction to Information Visualization: Transforming Data into Meaningful Information is for anyone interested in the art and science of communicating data to others. It shows readers how to transform data into something meaningful - information. Applying information visualization in research, service, teaching, and professional life requires a solid understanding of graphic design and the aesthetic along with hands-on skills and knowledge of data principles and software. This book is applicable to students in all domains, to researchers who need to understand how to create graphics that explain their data, and to professionals and administrators for professional development training. Website Designers and Human-Computer Interaction researchers will appreciate the backstory of designing interactive visualizations for the web. Drawing on the author’s years of practice and teaching, it bridges the two worlds in ways everyone can participate in the future of information and to appreciate the beautiful in information: Step-by-step directions in the fundamentals of HTML5, CSS, and d3.js Design challenges with fully explained answers Web-site support for code samples (JavaScript, d3.js, python), live examples, and a place to build a community of other IV pros Useful for teaching design to scientists; data to the humanities Guidance for using the text depending on the class makeup Review of third-party visualization software, big data trends, and script libraries Guidance on how to continue in the IV world after graduation This full-color book features graphics and a companion Web site. The online companion site hosts living examples, updates, and errata. You’re invited to participate on the site, too, sharing your questions, solutions, and ideas. For most readings, there is a partner design lab. At the conclusion of the course, there is a complete interactive information visualization service documentation for libraries.