Wrapping Up. Chapter 3: Choosing Tools to Visualize Chapter 4: Visualizing Patterns over. Time such as Needlebase and Able2Extract PDF converter. The language of law school: learning to “think like a lawyer” / Elizabeth Mertz grounded in the study of the lang Art Models 4: Life Nude Photos for the Visual . View Table of Contents for Visualize This. Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Author(s). Nathan Yau. First published:6 Summary · PDF · Request permissions · xml. CHAPTER 1.

Author:SHAKIA GUILIANELLI
Language:English, Spanish, Arabic
Country:Uganda
Genre:Lifestyle
Pages:691
Published (Last):17.02.2016
ISBN:623-2-57221-771-9
Distribution:Free* [*Registration Required]
Uploaded by: PASQUALE

69737 downloads 170165 Views 30.66MB PDF Size Report


Visualize This Pdf

Practical data design tips from a data visualization expert ofthe modern age Data doesn?t decrease; it is ever-increasing and can beoverwhelming to organize in. Visualize this nathan yau pdf. Free Pdf Download 21 31 54 -A- C. Windows system32 fontsub. Visualize this nathan yau pdf. Novel visualization techniques from the. Visualize This! competition. Alex Razoumov [email protected] WestGrid / Compute Canada.

Sommaruga supsi. The Star Resource Navigator is an ontology based tool to visualize, navigate and search web distributed RDF resources. Resources and their connections are graphically represented as a star connected graph with labels indicating the existing relations. The Navigator has been tested in different application domains, coded by means of different ontologies. Because of its intuitive and easy to use interface, the system is oriented to end-users who are not Semantic Web experts. After a brief analysis of existing tools and techniques to visualize RDF structures, the paper describes the Star Resource Navigator, as an example of intuitive environment for resource navigation and visualization. While the process of marking content with metadata can be accomplished by using these formal languages, a remaining important issue is how to visualize this information.

Among the third group of strategies, computational methods are used to map global 3D genome structures at various scales driven by experimental data such as 3C-coupled sequencing data or by basic assumption of physical properties such as polymer models of chromosomal regions; see review Fudenberg and Mirny ; Varoquaux et al.

In this review, we will mainly focus on the recent progress of some novel bioimaging methods and computational visualization techniques that are important for the second and third strategies mentioned above.

We will first introduce imaging methods used to label and image genomic data in fixed cells, such as in situ hybridization ISH methods based on long fluorescent probes, short oligo probes, and molecular beacons. Next, we will present the methods used for imaging genomic loci in live cells.

Visualize This: The FlowingData Guide to Design, Visualization, and Statistics

Because the fluorescence-capturing capability of a particular microscope is very important for the sensitivity of bioimaging experiments, we next provide a short introduction to the two novel super-resolution microscopy methods developed by us recently, polarized super-resolution microscopy PSRM and low-power super-resolution stimulated emission depletion STED microscopy.

Then, we review the development of some visualization tools used for 3D genome study, with a focus on the two viewers developed recently: Web3DMol and HiC-3DViewer. We conclude with a discussion and a short outlook on future development, including how to integrate these strategies together. Imaging 3D genomes in fixed cells Imaging genomic loci with long probes Before the advent of molecular techniques such as 3C chromosome conformation capture Dekker et al.

Developing DNA sequence-specific labeling methods is required to understand any potential relationship between DNA sequence information such as that of genes, regulatory elements and their positioning within the nucleus. Since it was first invented in the s Langer-Safer et al.

The sensitivity of FISH experiments depends on the fluorescence signal intensity of the probes, the signal-to-noise ratio between the targets and background, and the labeling efficiency, as well as the fluorescence-capturing capability of a particular microscope.

The size of the fluorescent probe and its target region are directly proportional to the strength of the signals. The long probes library generated from nick translation Pinkel et al. Biological findings regarding the chromatin architecture at the chromosome level, such as visualizing chromatin territories and interchromatin space Bolzer et al.

Hogan et al. However, the genomic sequence resolution, that is, the ability to distinguish two separate loci along a chromosome, is compromised by the size of long probes.

Open image in new window Fig. Loci in the paternal-origin chromosome showed specific localization lower left which is absent in the maternal-origin chromosome lower right image modified from Tang et al. The position of each TAD is plotted as red dot in the microscopy image left and in 3D right image modified from Wang et al.

Imaging genomic loci with short probes Short probe development and utilization in DNA labeling depends greatly on the various approaches in synthesizing fluorophore-tagged oligonucleotides oligos. Because it is expensive to custom-synthesize hundreds of fluorescent oligos separately to label one specific loci, they were more frequently used to label specific genomic regions with highly repetitive sequence motifs such as in telomeres and centromeres Matera and Ward Different single-strand oligo probe synthesis strategies with lower production costs and simplified procedures were proposed to promote the use of these probes in FISH experiments Beliveau et al.

With such PCR-based preparation, the target size of the probe could be adjusted freely as long as the total fluorescence intensity generated by the probe pool could be distinguished from background under microscopy. While Boyle et al. To improve the hybridization efficiency of small genomic loci, Beliveau et al. As an alternative to intensify signals by using a secondary intensifying probe, Ni et al. The self-complementarity of MB probes reduced false positive signals introduced by leftover non-specific binding probes and hence increased the signal-to-noise ratio, allowing the detection and 3D depiction of specific DNA loci as short as 2.

With high labeling efficiency and sequence-resolution, short non-repetitive genome segments such as cis-regulatory elements enhancers and promoters whose size is normally only approximately a few kb, can be effectively visualized. The MB-FISH method can also be utilized to visualize multiple loop interactions and delineate the pairwise interactions in single cells with high resolution. Cremer et al. Because two sets of differently labeled probes are needed to reliably target a small genomic region at one time, this method might be less versatile in co-labeling of multiple targets considering the total available fluorescent dyes.

Nanotechnology holds great potential for the study of genome structure. Semiconductor nanocrystals, i. Pathak et al. However, these direct-labeled QD probes usually require chemical synthesis, which limits their adaptation. Xiao et al. Muller et al. However, it remains challenging to fully potentiate nanoparticles including QD, surface-enhanced Raman scattering nanoparticles, upconversion nanoparticles, and silica nanoparticles for chromatin labeling due to their low reliability and consistency in quality control Ioannou and Griffin The size and surface chemistry of each nanoparticle should be uniformly synthesized and well-adjusted to fit in a special biological sample.

On the other hand, micro- and nano-devices have been successfully adopted to probe epigenomic states and chromatin interactions Aguilar and Craighead , as well as single-cell sequencing Blainey and Quake Considerable effort has been made to preserve the nucleus morphology and chromatin ultra-structure during FISH procedures Markaki et al.

However, it should be noted that the DNA ultrastructure at the level of nano-resolution might still be distorted. Hence, the development of DNA labeling methods without the need for heat denaturation is still the focus of great anticipation. Short peptide nucleic acid PNA probes have been used to label specific repetitive DNA sequences in situ mostly telomere, centromere without a heat denaturation step Genet et al.

Unfortunately, considering the cost for the synthesis of PNA probes, people generally do not consider PNA a practical method. Therefore, developing novel imaging tools to image and to track individual chromatin-interacting RNAs will be helpful to understand how 3D genome organization helps gene regulation and transcription.

The first RNA FISH probes were modified nucleotides that incorporated antisense RNA generated from plasmid templates and were further targeted by antibodies that could be labeled and imaged Langer et al.

By improving this oligo probe-based technique in terms of the size of the probe set and probe length, RNA FISH can be used to detect multiple RNA species in the same individual cells at the same time Raj et al.

Apart from using multiple linear singly labeled probes, other probe designs, such as molecular beacon Tyagi and Kramer and branching DNA amplification Player et al. Based on these strategies, further refinements have been focused on multiplexing the RNA labeling capability and improving the RNA molecule imaging resolution, providing resourceful means for RNA studies Lubeck and Cai Imaging 3D genomes in live cells 3D genome regulation is a dynamic process.

Although FISH-based methods can capture a detailed chromatin architecture at a specific moment, they cannot monitor any potential dynamic changes. Therefore, a method to image specific genomic loci in live cells is indispensable. Fluorescent proteins fused with native DNA-binding proteins were first utilized to label DNA sequences, but the versatility and effectiveness of this approach were restricted to the limited choice of available DNA-binding proteins Robinett et al.

How these networks function internally, however, is often not well understood.

PDF - Visualize This

Advances in understanding DNNs will benefit and accelerate the development of the field. We present TNNVis, a visualization system that supports understanding of deep neural networks specifically designed to analyze text.

It integrates visual encodings and interaction techniques chosen specifically for our tasks. The tool allows users to: 1 visually explore DNN models with arbitrary input using a combination of node—link diagrams and matrix representation; 2 quickly identify activation values, weights, and feature map patterns within a network; 3 flexibly focus on visual information of interest with threshold, inspection, insight query, and tooltip operations; 4 discover network activation and training patterns through animation; and 5 compare differences between internal activation patterns for different inputs to the DNN.

These functions allow neural network researchers to examine their DNN models from new perspectives, producing insights on how these models function.

Clustering and summarization techniques are employed to support large convolutional and fully connected layers. Based on several part of speech models with different structure and size, we present multiple use cases where visualization facilitates an understanding of the models.

Dengue Fever Surveillance in India Using Text Mining in Public Media Despite the improvement in health conditions across the world during the past decades, communicable diseases remain among the leading mortality causes in many countries. Combating communicable diseases depends on surveillance, preventive measures, outbreak investigation and the establishment of control mechanisms.

Delays in obtaining country level data of confirmed communicable diseases cases, like dengue fever, are prompting new efforts for short- to medium-term data. News articles highlight dengue infections and they can reveal how public health messages, expert findings, and uncertainties are communicated to the public. In this paper, we analyze dengue news articles in Asian countries, with a focus in India, for each month in We investigate how the reports cluster together, and uncover how dengue cases, public health messages and research findings are communicated in the press.

Our main contributions are to: 1 uncover underlying topics from news articles that discuss dengue in Asian countries in ; 2 construct topic evolution graphs through the year; and 3 analyze the life cycle of dengue news articles in India, then relate them to rainfall, monthly reported dengue cases, and the Breteau Index. We show that the five main topics discussed in the newspapers in Asia in correspond to: 1 prevention; 2 reported dengue cases; 3 politics; 4 prevention relative to other diseases; and 5 emergency plans.

We identify that rainfall has 0. Based in our findings, we conclude that the proposed method facilitates in the effective discovery of evolutionary dengue themes and patterns. Villanes, A.

The Utility of Beautiful Visualizations Geovisualizations provide a means to inspect large complex multivariate datasets for information that would not otherwise be available with a tabular view or summary statistics alone.

Aesthetically appealing visualizations can elicit prolonged exploration and encourage discovery. Creating data geovisualizations that are effective and beautiful is an important yet difficult challenge. Here we present a tool for rendering geovisualizations of continuous spatial data using impressionist painterly techniques.

The techniques, which have been tested in controlled studies, vary the visual properties e. To demonstrate this technique, we render two examples: 1 weather data attributes e. These examples demonstrate how open source geospatial visualizations can harness aesthetics to enhance visual communication and viewer engagement.

Tateosian, L. A tracking and automatic color adjustment system are designed so that the device can work robustly with noisy surroundings and is invariant to changes in lighting and background noise. A user study of 3D rotation tasks shows that the device outperforms other 6 DoF input devices used in a similar desktop environment.

The device has the potential to facilitate interactive applications such as games as well as viewing 3D information. Chen, Z. Amant, R. Real-Time Independent Rasterization for Multi-View Rendering Multi-view soft shadows rendered using: left traditional multi-pass rasterization; right view-independent rasterization VIR paired with parallel view rendering, both methods produce high quality shadow penumbra, but VIR requires only a fraction of the time Existing graphics hardware parallelizes view generation poorly, placing many multi-view effects—such as soft shadows, defocus blur, and reflections—out of reach for real-time applications.

We present emerging solutions that address this problem using a high density point set tailored per frame to the current multi-view configuration, coupled with relatively simple reconstruction kernels. Points are a more flexible rendering primitive, which we leverage to render many high resolution views in parallel. Marrs, A. Large Image Collection Visualization Using Perception-Based Similarity with Color Features This paper introduces the basic steps to build a similarity-based visualization tool for large image collections.

We build the similarity metric s based on human perception. Psychophysical experiments have shown that human observers can recognize the gist of scenes within milliseconds msec by comprehending the global properties of an image. Color also plays an important role in human rapid scene recognition. However, previous works often neglect color features.

We propose new scene descriptors that preserve the information from coherent color regions, as well as the spatial layouts of scenes. Experiments show that our descriptors outperform existing state-of-the-art approaches. Given the similarity metrics, a hierarchical structure of an image collection can be built in a top-down manner.

Representative images are chosen for image clusters and visualized using a force-directed graph. Applying Impressionist Painterly Techniques to Data Visualization An important task of science is to communicate complex data to peers and the public.

Here we ask whether harnessing the painterly techniques of impressionist-era painters is beneficial. In two experiments, participants viewed weather maps from the International Panel of Climate Change that were rendered using either an industry-standard technique glyphs or one of three styles inspired from impressionist masters.

The glyph technique used rectangular glyphs that vary properties of color and texture e. For the impressionist styles, regions of maximum contrast in the underlying data were rendered using brushstroke algorithms to emphasize interpretational complexity two distinct layers of paint where unique regions have greater brushstroke overlap , indication and detail unique regions are rendered with increased brushstroke thickness and density , and visual complexity unique regions are rendered with different brushstrokes at a global level and reinforced with increased brushstroke variation at a local level.

Visual complexity was expected to be more memorable and allow for more accurate information extraction because it both draws attention to distinct image regions and engages the viewer at those locations with increased brushstroke variability.

In Experiment 1 thirty participants completed a new—old recognition test for which d-prime values of visual complexity and glyph were comparable, and both superior to the other styles.

Experiment 2 tested the accuracy of numerosity estimation with a different group of thirty participants and here visual complexity was superior above all other styles. An exit poll completed at the end of both studies further revealed that the style participants identified as being "most liked" associated with higher performance relative those not selected.

Incidental eye-tracking revealed impressionist styles elicited greater visual exploration over glyphs. These results offer a proof-of-concept that visualizations based on Impressionist brushstrokes can be memorable, functional, and engaging.

Pete Beach, FL 16, 12, , Visualizing Static Ensembles for Effective Shape and Data Comparison The challenges of cyber situation awareness call for ways to provide assistance to analysts and decision-makers. In many fields, analyses of complex systems and activities benefit from visualization of data and analytical products.

Analysts use images in order to engage their visual perception in identifying features in the data, and to apply the analysts' domain knowledge.

One would expect the same to be true in the practice of cyber analysts as they try to form situational awareness of complex networks. This chapter takes a close look at visualization for Cyber Situation Awareness. We begin with a basic overview of scientific and information visualization, and of recent visualization systems for cyber situation awareness. Then, we outline a set of requirements, derived largely from discussions with expert cyber analysts, for a candidate visualization system.

Hao, L. Effective Visualization of Temporal Ensembles An ensemble is a collection of related datasets, called members, built from a series of runs of a simulation or an experiment. Ensembles are large, temporal, multidimensional, and multivariate, making them difficult to analyze. Another important challenge is visualizing ensembles that vary both in space and time. Initial visualization techniques displayed ensembles with a small number of members, or presented an overview of an entire ensemble, but without potentially important details.

Recently, researchers have suggested combining these two directions, allowing users to choose subsets of members to visualization. This manual selection process places the burden on the user to identify which members to explore.

We first introduce a static ensemble visualization system that automatically helps users locate interesting subsets of members to visualize. We next extend the system to support analysis and visualization of temporal ensembles. We employ 3D shape comparison, cluster tree visualization, and glyph based visualization to represent different levels of detail within an ensemble. This strategy is used to provide two approaches for temporal ensemble analysis: 1 segment based ensemble analysis, to capture important shape transition time-steps, clusters groups of similar members, and identify common shape changes over time across multiple members; and 2 time-step based ensemble analysis, which assumes ensemble members are aligned in time by combining similar shapes at common time-steps.

Both approaches enable users to interactively visualize and analyze a temporal ensemble from different perspectives at different levels of detail. We demonstrate our techniques on an ensemble studying matter transition from hadronic gas to quark-gluon plasma during gold-on-gold particle collisions. Ensemble Visualization for Cyber Situation Awareness of Network Security Data Network security analysis and ensemble data visualization are two active research areas.

Although they are treated as separate domains, they share many common challenges and characteristics. Both focus on scalability, time-dependent data analytics, and exploration of patterns and unusual behaviors in large datasets. These overlaps provide an opportunity to apply ensemble visualization research to improve network security analysis. To study this goal, we propose methods to interpret network security alerts and flow traffic as ensemble members.

We can then apply ensemble visualization techniques in a network analysis environment to produce a network ensemble visualization system.

Including ensemble representations provide new, in-depth insights into relationships between alerts and flow traffic. Analysts can cluster traffic with similar behavior and identify traffic with unusual patterns, something that is difficult to achieve with high-level overviews of large network datasets. Furthermore, our ensemble approach facilitates analysis of relationships between alerts and flow traffic, improves scalability, maintains accessibility and configurability, and is designed to fit our analysts' working environment, mental models, and problem solving strategies.

Visualizations and Analysts The challenges of cyber situation awareness call for ways to provide assistance to analysts and decision-makers. Healey, C. Kott, C. Wang and R. Erbacher, Eds. Visualizing Likelihood Density Functions via Optimal Region Projection Effective visualization of high-likelihood regions of parameter space is severely hampered by the large number of parameter dimensions that many models have.

We present a novel technique, Optimal Percentile Region Projection, to visualize a high-dimensional likelihood density function that enables the viewer to understand the shape of the high-likelihood region. Optimal Percentile Region Projection has three novel components: first, we select the region of high likelihood in the high-dimensional space before projecting its shadow into a lower-dimensional projected space. Second, we analyze features on the surface of the region in the projected space to select the projection direction that shows the most interesting parameter dependencies.

Finally, we use a three-dimensional projection space to show features that are not salient in only two dimensions. The viewer can also choose sets of axes to project along to explore subsets of the parameter space, using either the original parameter axes or principal-component axes.

The technique was evaluated by our domain-science collaborators, who found it to be superior to their existing workflow both when there were interesting dependencies between parameters and when there were not.

Canary, H. Flexible Web Visualization for Alert-Based Network Security Analytics This paper describes a web-based visualization system designed for network security analysts at the U.

Our goal is to provide visual support to the analysts as they investigate security alerts for malicious activity within their systems. Our ARL collaborators identified a number of important requirements for any candidate visualization system. These relate to the analyst's mental models and working environment, and to the visualization tool's configurability, accessibility, scalability, and "fit" with existing analysis strategies.

To meet these requirements, we designed and implement a web-based tool that uses different types of charts as its core representation framework. A JavaScript charting library RGraph was extended to provide the interface extensibility and correlation capabilities needed to support analysts as they explore different hypotheses about a potential attack.

We describe key elements of our design, explain how an analyst's intent is used to generate different visualizations, and show how the system's interface allows an analyst to rapidly produce a sequence of visualizations to explore specific details about a potential attack as they arise.

We conclude with a discussion of plans to further improve the system, and to collect feedback from our ARL colleagues on its strengths and limitations in real-world analysis scenarios. On the Limits of Resolution and Visual Angle in Visualization This article describes a perceptual level-of-detail approach for visualizing data. Properties of a dataset that cannot be resolved in the current display environment need not be shown, for example, when too few pixels are used to render a data element, or when the element's subtended visual angle falls below the acuity limits of our visual system.

To identify these situations, we asked: 1 What type of information can a human user perceive in a particular display environment? To answer these questions, we conducted controlled experiments that identified the pixel resolution and subtended visual angle needed to distinguish different values of luminance, hue, size, and orientation.

This information is summarized in a perceptual display hierarchy, a formalization describing how many pixels—resolution—and how much physical area on a viewer's retina—visual angle—is required for an element's visual properties to be readily seen.

We demonstrate our theoretical results by visualizing historical climatology data from the International Panel for Climate Change. Interest Driven Navigation in Visualization This paper describes a new method to explore and discover within a large dataset. We apply techniques from preference elicitation to automatically identify data elements that are of potential interest to the viewer.

These "elements of interest" are bundled into spatially local clusters, and connected together to form a graph. The graph is used to build camera paths that allow viewers to "tour" areas of interest within their data.

It is also visualized to provide wayfinding cues. Our preference model uses Bayesian classification to tag elements in a dataset as interesting or not interesting to the viewer. The model responds in real-time, updating the elements of interest based on a viewer's actions. This allows us to track a viewer's interests as they change during exploration and analysis. Viewers can also interact directly with interest rules the preference model defines. We demonstrate our theoretical results by visualizing historical climatology data collected at locations throughout the world.

Attention and Visual Memory in Visualization and Computer Graphics A change blindness example, it is often difficult to immediately see the difference between the left and the right images. Once found, it is clear the difference is not subtle. Limits on visual memory make it difficult to compare the images.

A fundamental goal of visualization is to produce images of data that support visual analysis, exploration, and discovery of novel insights. An important consideration during visualization design is the role of human visual perception. This article surveys research on attention and visual perception, with a specific focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these findings form a foundation for more recent work on visual memory and visual attention.

We conclude with a brief overview of how knowledge of visual attention and visual memory is being applied in visualization and graphics. We also discuss how challenges in visualization are motivating research in psychophysics. Exploring Ensemble Visualization An ensemble is a collection of related datasets. Each dataset, or member, of an ensemble is normally large, multidimensional, and spatio-temporal. Ensembles are used extensively by scientists and mathematicians, for example, by executing a simulation repeatedly with slightly different input parameters and saving the results in an ensemble to see how parameter choices affect the simulation.

To draw inferences from an ensemble, scientists need to compare data both within and between ensemble members. We propose two techniques to support ensemble exploration and comparison: a pairwise sequential animation method that visualizes locally neighboring members simultaneously, and a screen door tinting method that visualizes subsets of members using screen space subdivision. We demonstrate the capabilities of both techniques, first using synthetic data, then with simulation data of heavy ion collisions in high-energy physics.

Results show that both techniques are capable of supporting meaningful comparisons of ensemble data. Phadke, M. Comparative Visualization of Ensembles Using Ensemble Surface Slicing By definition, an ensemble is a set of surfaces or volumes derived from a series of simulations or experiments. Sometimes the series is run with different initial conditions for one parameter to determine parameter sensitivity.

The understanding and identification of visual similarities and differences among the shapes of members of an ensemble is an acute and growing challenge for researchers across the physical sciences. More specifically, the task of gaining spatial understanding and identifying similarities and differences between multiple complex geometric data sets simultaneously has proved challenging.

This paper proposes a comparison and visualization technique to support the visual study of parameter sensitivity. ESS produces a single image that is useful for determining differences and similarities between surfaces simultaneously from several data sets. We demonstrate the usefulness of ESS on two real-world data sets from our collaborators.

Alabi, O. Visualizing Combinatorial Auctions Visualizing three stages in a combinatorial auction: concentric rings represent different bundles of goods, segment color and blur shows bid price and interest in a bundle, and white rectangles identify a "winning" bidder for a bundle; winning bids connected with dashed lines identify a competitive allocation of all goods in the auction We propose a novel scheme to visualize combinatorial auctions; auctions that involve the simultaneous sale of multiple items.

downloaders bid on complementary sets of items, or bundles, where the utility of securing all the items in the bundle is more than the sum of the utility of the individual items. Our visualizations use concentric rings divided into arcs to visualize the bundles in an auction. Keyframe animations are used to show changes in an auction over time. We demonstrate our visualization technique on a standard testbed dataset generated by researchers to evaluate combinatorial auction bid strategies, and on recent Federal Communications Commission FCC auctions designed to allocate wireless spectrum licenses to cell phone service providers.

Hsiao, J.

Interactive Visual Summarization of Multidimensional Data Visualization has become integral to the knowledge discovery process across various domains. However, challenges remain in the effective use of visualization techniques, especially when displaying, exploring and analyzing large, multidimensional datasets, such as weather and meteorological data. Direct visualizations of such datasets tend to produce images that are cluttered with excess detail and are ineffective at communicating information at higher levels of abstraction.

Subscribe to RSS

To address this problem we provide a visual summarization framework to intuitively reduce the data to its important and relevant characteristics. Summarization is performed in three broad steps. Next, patterns, relationships and outliers are extracted from the reduced data.

Finally, the extracted summary characteristics are visualized to the user. Such visualizations reduce excess visual detail and are more suited to the rapid comprehension of complex data. Users can interactively guide the summarization process gaining insight into both how and why the summary results are produced. Our framework improves the benefits of mathematical analysis and interactive visualization by combining the strengths of the computer and the user to generate high-quality summaries.

Initial results from applying our framework to large weather datasets have been positive, suggesting that our approach could be beneficial for a wide range of domains and applications. Kocherlakota, S.

Visual Perception and Mixed-Initiative Interaction For Assisted Visualization Design This paper describes the integration of perceptual guidelines from human vision with an AI-based mixed-initiative search strategy. The result is a visualization assistant called ViA, a system that collaborates with its users to identify perceptually salient visualizations for large, multidimensional datasets.

ViA applies knowledge of low-level human vision to: 1 evaluate the effectiveness of a particular visualization for a given dataset and analysis tasks; and 2 rapidly direct its search towards new visualizations that are most likely to offer improvements over those seen to date.

Context, domain expertise, and a high-level understanding of a dataset are critical to identifying effective visualizations. We apply a mixed-initiative strategy that allows ViA and its users to share their different strengths and continually improve ViA's understanding of a user's preferences.

We visualize historical weather conditions to compare ViA's search strategy to exhaustive analysis, simulated annealing, and reactive tabu search, and to measure the improvement provided by mixed-initiative interaction. We also visualize intelligent agents competing in a simulated online auction to evaluate ViA's perceptual guidelines. Results from each study are positive, suggesting that ViA can construct high-quality visualizations for a range of real-world datasets.

Visualizing Multidimensional Query Results Using Animation Effective representation of large, complex collections of information datasets presents a difficult challenge. Visualization is a solution that uses a visual interface to support efficient analysis and discovery within the data.

Our primary goal in this paper is a technique that allows viewers to compare multiple query results representing user-selected subsets of a multidimensional dataset.

We present an algorithm that visualizes multidimensional information along a space-filling spiral. Graphical glyphs that vary their position, color, and texture appearance are used to represent attribute values for the data elements in each query result.

Guidelines from human perception allow us to construct glyphs that are specifically designed to support exploration, facilitate the discovery of trends and relationships both within and between data elements, and highlight exceptions.

A clustering algorithm applied to a user-chosen ranking attribute bundles together similar data elements. This encapsulation is used to show relationships across different queries via animations that morph between query results.

We apply our techniques to the MovieLens recommender system, to demonstrate their applicability in a real-world environment, and then conclude with a simple validation experiment to identify the strengths and limitations of our design, compared to a traditional side-by-side visualization.

Sawant, A. ChipViz: Visualizing Memory Chip Test Data This paper presents a technique that allows test engineers to visually analyze and explore within memory chip test data.

We represent the test results from a generation of chips along a traditional grid and a spiral. We also show correspondences in the test results across multiple generations of memory chips. We use simple geometric "glyphs" that vary their spatial placement, color, and texture properties to represent the critical attribute values of a test. When shown together, the glyphs form visual patterns that support exploration, facilitate discovery of data characteristics, relationships, and highlight trends and exceptions in the test data that are often difficult to identify with existing statistical tools.

Weaving Versus Blending: A Quantitative Assessment of the Information Carrying Capacities of Two Alternative Methods for Conveying Multivariate Data With Color In many applications, it's important to understand the individual values of, and relationships between, multiple related scalar variables defined across a common domain. Several approaches have been proposed for representing data in these situations.

In this paper we focus on strategies for the visualization of multivariate data that rely on color mixing.

Related articles:


Copyright © 2019 terney.info.
DMCA |Contact Us