KEYWORDS: Visualization, Data mining, Information visualization, Human-machine interfaces, Data modeling, Data storage, Data archive systems, C++, Databases, Visual analytics
Data repositories around the world hold many thousands of datasets. A problem for remote dataset users is to browse the repositories and efficiently locate relevant datasets. In this note, we introduce the Iconic Remote Visual Data Exploration tool (IRVDX), which provides visual browsing for exploring the features of remote and distributed data without the necessity of downloading the entire dataset. IRVDX employs three kinds of visualizations: one provides a reduced representation of the datasets, which we call Dataset Icons. These icons show the important statistical characteristics of datasets and help to identify relevant datasets from distributed repositories. Another one is called the Remote Dataset Visual Browser that provides visualizations to browse remote data without downloading the complete dataset to identify its content. The final one provides visualizations to show the degree of similarity between two datasets and to visually determine whether a join of two remote datasets will be meaningful. In this paper, we describe the design and implementation of IRVDX in detail. We assess the benefits of our Dataset Icons against the traditional text-based interfaces and show the usefulness of IRVDX by conducting experiments with datasets from the UCI KDD Archive.
This paper describes the design and construction of a new visualization system for collections of heterogeneous
information for intelligence analysis. The system has several novel features that taken together provide a highly
modular and reusable framework for creating linked visual metaphors. The system leverages modern web
technologies such as XML DOM and Schemas to create an expressive and powerful system. Examples of this are
the ability to use the structure of the information being visualized (as expressed in an XML schema) to directly
generate the object oriented code for manipulating that information, and the use of static and dynamic binding
facilities for creating mappings between internal information items and visualization components. The resulting
system blurs the distinction between information visualization and the World Wide Web. It is very modular and
flexible, and supports rapid iteration and refinement of input data sources as well as interoperability with other
information schemas. New linked visual metaphors can easily be added to the framework as required.
We report on photodynamically induced inactivation of the skin bacterium Propionibacterium acnes (P. acnes) using endogenous as well as exogenous photosensitizers and red light sources. P. acnes is involved in the pathogenesis of the skin disease acne vulgaris. The skin bacterium is able to synthesize the metal-free fluorescent porphyrins protoporphyrin IX (PP) and coproporphyrin (CP) as shown by in situ spectrally-resolved detection of natural autofluorescence of human skin and bacteria colonies. These naturally occurring intracellular porphyrins act as efficient endogenous photosensitizers. Inactivation of P. acnes suspensions was achieved by irradiation with He-Ne laser light in the red spectral region (632.8 nm). We monitored the photodynamically-induced death of single bacteria using a fluorescent viability kit in combination with confocal laser scanning microscopy. In addition, the photo-induced inactivation was calculated by CFU (colony forming units) determination. We found 633 nm-induced inactivation (60 mW, 0.12 cm2 exposure area, 1 hour irradiation) of 72% in the case of non-incubated bacteria based on the destructive effect of singlet oxygen produced by red light excited endogenous porphyrins and subsequent energy transfer to molecular oxygen. In order to achieve a nearly complete inactivation within one exposure procedure, the exogenous photosensitizer Methylene Blue (Mb) was added. Far red exposure of Mb-labeled bacteria using a krypton ion laser at 647 nm and 676 nm resulted in 99% inactivation.
Seenet is a system for network visualization in which statistics that describe the operation of a network can be displayed graphically. In this system, a network is presented on a computer screen along with various user-operated sliders, buttons, and toggles that allow direct manipulation of the display, in order to reveal information about the state of the network. The user interface was designed to promote rapid interaction and ease of use, which are critical to the success of this system. Features of Seenet include: a screen design in which most of the area is utilized for the network display, color usage that is consistent and meaningful, mouse actions on the network display to bring up auxiliary information, a novel 2-sided slider, animation for showing time sequences, and 'brushing' for selecting subsets of the network nodes.
Conference Committee Involvement (3)
Visualization and Data Analysis 2010
18 January 2010 | San Jose, California, United States
Visualization and Data Analysis 2009
19 January 2009 | San Jose, California, United States
Visualization and Data Analysis 2008
28 January 2008 | San Jose, California, United States
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