Science Of Analytical Reasoning Research Articles

Visual analytics for immunologists: Data compression and fractal distributions

Visual analytics is the science of analytical reasoning that facilitates research through the use of interactive visual interfaces. New techniques of visual analytics are designed to aid the understanding of complex systems versus traditional blind-context rules to explore massive volumes of interrelated data. Nowhere else is visualization more important in analysis than in the emerging fields of life sciences, where amounts of collected data grow increasingly in exponential rates.The complexity of the immune system in immunology makes visual analytics especially important for understanding how this system works. In this context, our effort should be focused on avoiding accurate but potentially misleading use of visual interfaces. The proposed approach of data compression and visualization that reveal structural and functional features of immune responses enhances systemic and comprehensive description and provides the platform for hypothesis generation. Further, this approach can evolve into a powerful visual-analytical tool for prospective and real-time monitoring and can provide an intuitive and interpretable illustration of vital dynamics that govern immune responses in an individual and populations.The undertaken explorations demonstrate the critical role of novel techniques of visual analytics in stimulating research in immunology and other life sciences and in leading us to understanding of complex biological systems and processes.

Science of Analytical Reasoning

There has been progress in the science of analytical reasoning and in meeting the recommendations for future research that were laid out when the field of visual analytics was established. Researchers have also developed a group of visual analytics tools and methods that embody visual analytics principles and attack important and challenging real-world problems. However, these efforts are only the beginning and much study remains to be done. This article examines the state of the art in visual analytics methods and reasoning and gives examples of current tools and capabilities. It shows that the science of visual analytics needs interdisciplinary efforts, indicates some of the disciplines that should be involved and presents an approach to how they might work together. Finally, the article describes some gaps, opportunities and future directions in developing new theories and models that can be enacted in methods and design principles and applied to significant and complex practical problems and data.

Visual Analytics Science and Technology

It is an honor to welcome you to the first theme issue of information visualization (IVS) dedicated entirely to the study of visual analytics. It all started from the establishment of the U.S. Department of Homeland Security (DHS) sponsored National Visualization and Analytics Center™ (NVAC™) at the Pacific Northwest National Laboratory (PNNL) in 2004. In 2005, under the leadership of NVAC, a team of the world’s best and brightest multidisciplinary scholars coauthored its first research and development (R&D) agenda Illuminating the Path, which defines the study as “the science of analytical reasoning facilitated by interactive visual interfaces.” Among the most exciting, challenging, and educational events developed since then was the first IEEE Symposium on Visual Analytics Science and Technology (VAST) held in Baltimore, Maryland in October 2006. This theme issue features seven outstanding articles selected from the IEEE VAST proceedings and a commentary article contributed by Jim Thomas, the director of NVAC, on the status and progress of the center.

Guest Editorial: Special Section on Visual Analytics

ISUAL analytics is the science of analytical reasoning supportedbyhighlyinteractivevisualinterfaces.People use visual analytics tools and techniques to synthesize information; derive insight from massive, dynamic, and often conflicting data; detect the expected and discover the unexpected; provide timely, defensible, and understandable assessments; and communicate assessments effectively for action. The issues stimulating this body of research provide a grandchallengeinscience:turninginformationoverloadinto the opportunity of the decade. Visual analytics requires interdisciplinary science beyond traditional scientific and information visualization to include statistics, mathematics, knowledge representation, management and discovery technologies, cognitive and perceptual sciences, decision sciences, and more. An important research agenda to develop the next generation suite of visual analytics technologies is described in the book Illuminating the Path: The Research and Development Agenda for Visual Analytics, which is available at http:// nvac.pnl.gov/agenda.stm. The papers in this special section address a number of the issues described in the visual analytics research agenda. They are grouped into five major areas: multidimensional data, graphs and networks, communication network analysis, space and time, and fundamentals. The first two papers address issues of visual analysis of multidimensional data. The first paper, “High-Dimensional