scholarly journals Manipulações estatísticas e anomalias visuais: design de visualização de dados e reconhecimento de vieses estatísticos | Statistical manipulations and visual anomalies: data visualization design and statistical bias recognition

2020 ◽  
Vol 17 (2) ◽  
pp. 145-162
Author(s):  
Jaqueline Vasconcelos Braga ◽  
Tiago Barros Pontes e Silva ◽  
Virgínia Tiradentes Souto
Keyword(s):  
Data Visualization ◽  
Large Volume ◽  
Visual Information ◽  
Graphical Representations ◽  
Statistical Bias ◽  
Contemporary World ◽  
Information Bias ◽  
Visual Understanding ◽  
Visual Bias ◽  
Search Bias

O mundo contemporâneo é caracterizado por um amplo volume de informações produzidas. Contudo, proceder a seleção e leitura dessas informações por meio de relatos de pesquisa ou de notícias ainda é um desafio. Entre os obstáculos presentes se destacam os vieses da informação, originados por tratamentos de jornalistas ou pesquisadores, ou mesmo provocados intencionalmente para subverter a representação da realidade a partir dos dados obtidos. Assim, o presente estudo visa discutir a interpretação de informações visuais em representações gráficas de cálculos estatísticos de modo a contextualizar alguns dos principais recursos visuais de enviesamento de pesquisa. Para tanto, aborda os principais modos de enviesamento em pesquisas a partir das representações da estatística e da visualização de dados e identifica alguns passos nos quais o enviesamento se traduz em informações visuais. A partir do levantamento realizado, sugere-se que a compreensão visual dos recursos de visualização de dados pode ao menos instigar a indagação do leitor acerca do possível viés.*****The contemporary world is characterized by a large volume of produced information. However, selecting and reading this information through research reports or news is still a challenge. Among the present obstacles stand out the information bias, originated by treatments of journalists or researchers, or even intentionally provoked to subvert the representation of reality from the obtained data. Thus, the present study aims to discuss the interpretation of visual information in graphical representations of statistical calculations in order to contextualize some of the main visual bias features of research. To this end, it addresses the main modes of search bias from statistical representations and data visualization and identifies some steps in which bias translates into visual information. From the study, it is suggested that the visual understanding of data visualization resources may at least instigate the reader's question about the possible bias.

Reducing misperceptions through news stories with data visualization: The role of readers’ prior knowledge and prior beliefs

Journalism ◽  
2021 ◽  
pp. 146488492110287
Author(s):  
Paul Mena
Keyword(s):  
Experimental Design ◽  
Prior Knowledge ◽  
Data Visualization ◽  
Accurate Information ◽  
Graphical Representations ◽  
Prior Beliefs ◽  
News Stories ◽  
Issue Involvement

Amid the global discussion on ways to fight misinformation, journalists have been writing stories with graphical representations of data to expose misperceptions and provide readers with more accurate information. Employing an experimental design, this study explored to what extent news stories correcting misperceptions are effective in reducing them when the stories include data visualization and how influential readers’ prior beliefs, issue involvement and prior knowledge may be in that context. The study found that the presence of data visualization in news articles correcting misperceptions significantly enhanced the reduction of misperceptions among news readers with less than average prior knowledge about an issue. In addition, it was found that prior beliefs had a significant effect on news readers’ misperceptions regardless of the presence or absence of data visualization. In this way, this research offers some support for the notion that data visualization may be useful to decrease misperceptions under certain circumstances.

scholarly journals Performance Data Visualization of Linux Events on Multicores

2021 ◽  
Author(s):  
Claudio Scheer ◽  
Renato B. Hoffmann ◽  
Dalvan Griebler ◽  
Isabel H. Manssour ◽  
Luiz G. Fernandes
Keyword(s):  
Data Visualization ◽  
Large Volume ◽  
Real World ◽  
Interactive Visualization ◽  
Performance Data ◽  
Optimization Process ◽  
Parallel Applications ◽  
Storage Space ◽  
Tool Chain ◽  
Real World Application

Profiling tools are essential to understand the behavior of parallel applications and assist in the optimization process. However, tools such as Perf generate a large amount of data. This way, they require significant storage space, which also complicates reasoning about this large volume of data. Therefore, we propose VisPerf: a tool-chain and an interactive visualization dashboard for Perf data. The VisPerf tool-chain profiles the application and pre-processes the data, reducing the storage space required by about 50 times. Moreover, we used the visualization dashboard to quickly understand the performance of different events and visualize specific threads and functions of a real-world application.

scholarly journals Changes in Cortical Thickness in 6-Year-Old Children Open Their Mind to a Global Vision of the World

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Nicolas Poirel ◽  
Elise Leroux ◽  
Arlette Pineau ◽  
Olivier Houdé ◽  
Grégory Simon
Keyword(s):  
Cortical Thickness ◽  
Visual Information ◽  
The Other ◽  
Global Information ◽  
Healthy Children ◽  
The World ◽  
Global Vision ◽  
Global Perception ◽  
Visual Bias ◽  
Synaptic Pruning

Even if objectively presented with similar visual stimuli, children younger than 6 years of age exhibit a strong attraction to local visual information (e.g., the trees), whereas children older than 6 years of age, similar to adults, exhibit a visual bias toward global information (e.g., the forest). Here, we studied the cortical thickness changes that underlie this bias shift from local to global visual information. Two groups, matched for age, gender, and handedness, were formed from a total of 30 children who were 6 years old, and both groups performed a traditional global/local visual task. The first group presented a local visual bias, and the other group presented a global visual bias. The results indicated that, compared with the local visual bias group, children with a global visual bias exhibited (1) decreased cortical thickness in the bilateral occipital regions and (2) increased cortical thickness in the left frontoparietal regions. These findings constitute the first structural study that supports the view that both synaptic pruning (i.e., decreased cortical thickness) and expansion mechanisms (i.e., increased cortical thickness) cooccur to allow healthy children to develop a global perception of the visual world.

scholarly journals Examining data visualization pitfalls in scientific publications

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Vinh T Nguyen ◽  
Kwanghee Jung ◽  
Vibhuti Gupta
Keyword(s):  
Data Visualization ◽  
Spatial Orientation ◽  
Graphical Representation ◽  
Critical Issue ◽  
Graphical Representations ◽  
Scientific Publications ◽  
Full Force ◽  
Pie Chart ◽  
Fundamental Units

AbstractData visualization blends art and science to convey stories from data via graphical representations. Considering different problems, applications, requirements, and design goals, it is challenging to combine these two components at their full force. While the art component involves creating visually appealing and easily interpreted graphics for users, the science component requires accurate representations of a large amount of input data. With a lack of the science component, visualization cannot serve its role of creating correct representations of the actual data, thus leading to wrong perception, interpretation, and decision. It might be even worse if incorrect visual representations were intentionally produced to deceive the viewers. To address common pitfalls in graphical representations, this paper focuses on identifying and understanding the root causes of misinformation in graphical representations. We reviewed the misleading data visualization examples in the scientific publications collected from indexing databases and then projected them onto the fundamental units of visual communication such as color, shape, size, and spatial orientation. Moreover, a text mining technique was applied to extract practical insights from common visualization pitfalls. Cochran’s Q test and McNemar’s test were conducted to examine if there is any difference in the proportions of common errors among color, shape, size, and spatial orientation. The findings showed that the pie chart is the most misused graphical representation, and size is the most critical issue. It was also observed that there were statistically significant differences in the proportion of errors among color, shape, size, and spatial orientation.

POVScript+: a program for model and data visualization using persistence of vision ray-tracing

2003 ◽  
Vol 36 (3) ◽  
pp. 944-947 ◽  
Author(s):  
T. D. Fenn ◽  
D. Ringe ◽  
G. A. Petsko
Keyword(s):  
Structural Analysis ◽  
Ray Tracing ◽  
Electron Density ◽  
Data Visualization ◽  
Visual Information ◽  
Three Dimensional ◽  
Input Output ◽  
High Quality ◽  
Rank Tensor ◽  
Volumetric Rendering

Macromolecular visualization is hampered by the fragmented set of available programs and the lack of cooperativity among them. The amount of visual information required for robust structural analysis is relatively difficult to generate and rarely allows further high-quality three-dimensional graphic rendering. Here, a modification ofMolScript[Kraulis (1991).J. Appl. Cryst.24, 946–950] is presented which contains the capability of the originalMolScript, the ability to carry out a majority of the options available in most other crystallographic visualization packages, as well as several new features of its own.POVScript+(currently version 1.62) allows anisotropic displacement ellipsoid rendering (read in as a second-rank tensor from a PDB file), electron-density polygonization (in several formats derived from a `marching tetrahedra' approach), volumetric rendering of electron density and GRASP/MSMS surface-map input/output. Finally,POVRayoutput is supported (viaa modified version ofPovScript) to generate high-quality renderings that are easily modified for any of a number of purposes (e.g.animations or altered textures).POVScript+provides a marked increase in the amount of structural and atomic detail possible, while still allowing a straightforward means of generating this information.

scholarly journals Evidence for a visual bias when recalling complex narratives

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249950
Author(s):  
Rebecca Scheurich ◽  
Caroline Palmer ◽  
Batu Kaya ◽  
Caterina Agostino ◽  
Signy Sheldon
Keyword(s):  
Visual Information ◽  
Perceptual Content ◽  
Perceptual Information ◽  
Auditory Information ◽  
Visual Content ◽  
Visual Descriptors ◽  
Episodic Memories ◽  
Types Of Information ◽  
Verbatim Recall ◽  
Visual Bias

Although it is understood that episodic memories of everyday events involve encoding a wide array of perceptual and non-perceptual information, it is unclear how these distinct types of information are recalled. To address this knowledge gap, we examine how perceptual (visual versus auditory) and non-perceptual details described within a narrative, a proxy for everyday event memories, were retrieved. Based on previous work indicating a bias for visual content, we hypothesized that participants would be most accurate at recalling visually described details and would tend to falsely recall non-visual details with visual descriptors. In Study 1, participants watched videos of a protagonist telling narratives of everyday events under three conditions: with visual, auditory, or audiovisual details. All narratives contained the same non-perceptual content. Participants’ free recall of these narratives under each condition were scored for the type of details recalled (perceptual, non-perceptual) and whether the detail was recalled with gist or verbatim memory. We found that participants were more accurate at gist and verbatim recall for visual perceptual details. This visual bias was also evident when we examined the errors made during recall such that participants tended to incorrectly recall details with visual information, but not with auditory information. Study 2 tested for this pattern of results when the narratives were presented in auditory only format. Results conceptually replicated Study 1 in that there was still a persistent visual bias in what was recollected from the complex narratives. Together, these findings indicate a bias for recruiting visualizable content to construct complex multi-detail memories.

Virtual Reality in Visual Analytics of Large Datasets

2019 ◽  
pp. 252-266
Author(s):  
Sameera Khan
Keyword(s):  
Virtual Reality ◽  
Data Visualization ◽  
Large Volume ◽  
Visual Analytics ◽  
Large Datasets ◽  
Complex Data ◽  
Human Beings ◽  
It Use ◽  
Interactive Environment

Visual analytics can be defined as a representation of data in form of diagrams, charts, pictures, graphs, etc., whereas virtual reality is a term used for the simulated interactive environment that exploits multiple sense organs of human beings to perceive information. Both of these techniques are merged to create an interactive environment for data visualization and analysis. Often it happens that a large volume of data is complex to represent, so to represent large, congested, and complex data in a manageable and comprehensive form, visual analytics is the need of an hour. The chapter discusses the scope of visual analytics, the role of virtual reality in visual analytics, challenges in VA using VR, tools used to implement it, use, and applications.

Mode of Input in Long-Term Recognition

1977 ◽  
Vol 44 (3) ◽  
pp. 736-738 ◽  
Author(s):  
Neil H. Schwartz ◽  
A. Alexander Garabedian ◽  
Raymond S. Dean ◽  
Frank R. Yekovich
Keyword(s):  
Visual Information ◽  
Long Term Memory ◽  
Term Memory ◽  
Input Modality ◽  
Input Mode ◽  
Visual Bias

Recent research by Garabedian, Yekovich, Sherman, and Dean has demonstrated that recognition from long-term memory was superior for words presented visually over those presented auditorily. Because their results could have been influenced by the salience of the projected visual items, the present investigation attempted to eliminate the possible visual bias. 16 undergraduates were presented a list of nouns of mixed input modality and were tested 6 min. later for incidental recognition of input mode. The present data corroborated findings by Garabedian, et al. who postulated that subjects use some form of stored visual information when identifying the input mode of words.

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