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Mastering The Information Age - Solving Problems with Visual Analytics
The VisMaster book will soon be available in print form but you can download the full book at
www.vismaster.eu/book/.
This book is the result of a community effort of the partners of the VisMaster Coordinated Action funded by the European Union. The overarching aim of VisMaster was to create a research roadmap that outlines the current state of visual analytics across many disciplines, and to describe the next steps that have to be taken to foster a strong visual analytics community, thus enabling the development of advanced visual analytic applications.
The primary sources for this book are the final reports of the thematic working groups set up by the consortium. Each group focused on a particular aspect of visual analytics and brought together interested parties from a wide range of disciplines to collaborate on this task. The main authors of each chapter are given on each page, however there were contributions from many of the full, secondary and community partners as well as helpful comments and suggestions from external reviewers.
The first chapter introduces the problem space in terms of making sense of very large, complex datasets and outlines the vision for visual analytics. The second chapter looks at some application areas for visual analytics and then defines visual analytics in terms of the knowledge discovery process and considers the many scientific disciplines that contribute towards visual analytics. Chapters 3 to 8 present the work of the specialised working groups within the VisMaster consortium. Each of these chapters starts by giving an outline of the problem area and some relevant background information. case studies are presented which illustrate the use of knowledge discovery and data mining (KDD) in bioinformatics and climate change. The authors then pose the question of whether industry is ready for visual analytics, citing examples of the pharmaceutical, software and marketing industries.
Individual chapters can be downloaded separately.
Chapter 4: Data miningcase studies are presented which illustrate the use of knowledge discovery and data mining (KDD) in bioinformatics and climate change. The authors then pose the question of whether industry is ready for visual analytics, citing examples of the pharmaceutical, software and marketing industries. The state of the art section gives a comprehensive review of data mining/analysis tools such as statistical and mathematical tools, visual data mining tools, Web tools and packages. Some current data mining/visual analytics approaches are then described with examples from the bioinformatics and graph visualisation fields. Technical challenges specific to data mining are described such as achieving data cleaning, integration, data fusion etc. in real-time and providing the necessary infrastructure to support data mining.
Download chapter 4 PDF, 2.0MB