Information Visualization最新文献_第8页

VNLP: Visible natural language processing 可见自然语言处理

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-08-13 DOI: 10.1177/14738716211038898

Mohammad Alharbi, M. Roach, Tom Cheesman, R. Laramee

引用次数: 5

Not just a pretty picture: Scientific fact visualisation styles, preferences, confidence and recall 不仅仅是一张漂亮的图片:科学事实的视觉化风格、偏好、自信和回忆

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-07-01 DOI: 10.1177/14738716211027587

E. Walsh, G. Sargent, W. Grant

{"title":"Not just a pretty picture: Scientific fact visualisation styles, preferences, confidence and recall","authors":"E. Walsh, G. Sargent, W. Grant","doi":"10.1177/14738716211027587","DOIUrl":"https://doi.org/10.1177/14738716211027587","url":null,"abstract":"Visuals are often used to enhance learning of scientific information. The recent emergence and popularity of comic-style instruction books for adults, such as the ‘manga guide to …’, shows the possibility of comic style visualisations for the communication of science with adults. This study investigates whether the addition and style of visual accompaniment of scientific information, as used in comic books, influences immediate and short-term fact recall in an adult audience. Participants (n = 310 aged 18–79, 52% identified as female) were presented 20 general science facts in one of five styles: (1) text alone, (2) photo with text caption, (3) cartoon with text caption, (4) photo with explanatory agent and a speech bubble, (5) cartoon with explanatory agent and a speech bubble. Immediate recall, and confidence in that recall, was tested following a brief distractor. Participants indicated their preferred presentation style, and short-term recall was tested by a final quiz of all 20 facts. Overall, the most preferred presentation style was cartoon with explanatory agent and text in a speech bubble (26% preferred). There was no single most effective presentation style; there was no significant difference in immediate recall, short term recall or confidence in answers depending on whether the fact was presented as text, photo or cartoon, or the presence or absence of an explanatory agent. However, immediate recall was significantly better when preference was met (p < 0.02). We found that the style of visual accompaniment of scientific information in accordance with the ‘manga guide to…’ format influenced immediate, but not short-term, fact recall in an adult audience when written English literacy, scientific literacy and non-verbal intelligence were taken into account. Short term recall of scientific facts may best be served by presenting facts in multiple styles, or enquiring about and then meeting participant preference for visual accompaniment.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49152490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

MuzLink: Connected beeswarm timelines for visual analysis of musical adaptations and artist relationships MuzLink：连接蜂群时间线，用于音乐改编和艺术家关系的视觉分析

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-07-01 DOI: 10.1177/14738716211033246

F. Lévesque, Thomas Hurtut

{"title":"MuzLink: Connected beeswarm timelines for visual analysis of musical adaptations and artist relationships","authors":"F. Lévesque, Thomas Hurtut","doi":"10.1177/14738716211033246","DOIUrl":"https://doi.org/10.1177/14738716211033246","url":null,"abstract":"The rise of open data in the cultural domain is democratizing access to complex datasets usually presented as large multivariate and multilayered graphs. However, the exploration of such datasets is challenging for laypersons. The objective of this work is to develop and evaluate a new method for exploring and understanding a specific type of multilayered graph that combines a large bipartite graph with a set of tree structures. This paper proposes MuzLink, an interactive visualization tool that allows the user to navigate, search, locate, and compare collaborative and influential relationships between musical artists through the exploration of musical adaptations. The proposed tool is based on a set of connected timelines visualizing how an artist’s collaborations, inspirations, and influences evolved over time. This design study is conducted in close collaboration with BAnQ, the national library and archives agency of the Quebec government. A controlled user study, done with a group of BAnQ users, and two case studies, show how the proposed approach is capable of performing a considerable set of analytical and exploratory tasks.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/14738716211033246","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48917309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

PrAVA: Preprocessing profiling approach for visual analytics PrAVA：用于视觉分析的预处理评测方法

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-07-01 DOI: 10.1177/14738716211021591

Alessandra Maciel Paz Milani, Lucas Angelo Loges, F. Paulovich, I. Manssour

{"title":"PrAVA: Preprocessing profiling approach for visual analytics","authors":"Alessandra Maciel Paz Milani, Lucas Angelo Loges, F. Paulovich, I. Manssour","doi":"10.1177/14738716211021591","DOIUrl":"https://doi.org/10.1177/14738716211021591","url":null,"abstract":"To accommodate the demands of a data-driven society, we have expanded our ability to collect and store data, develop sophisticated algorithms, and generate elaborated visual representations of the data analysis process outcomes. However, data preprocessing, as the activity of transforming the raw data into an appropriate format for subsequent analysis, is still a challenging part of this process. Although we can find studies that address the use of visualization techniques to support the activities in the scope of preprocessing, the current Visual Analytics processes do not consider preprocessing an equally important phase in their processes. Hence, with this paper, we aim to contribute to the discussion of how we can incorporate the preprocessing as a prominent phase in the Visual Analytics process and promote better alternatives to assist the data analysts during the preprocessing activities. To achieve that, we are introducing the Preprocessing Profiling Approach for Visual Analytics (PrAVA), a conceptual Visual Analytics process that includes Preprocessing Profiling as a new phase. It also contemplates a set of guidelines to be considered by new solutions adopting PrAVA. Moreover, we analyze its applicability through use case scenarios that show resourceful methods for data understanding and evaluation of the preprocessing impacts. As a final contribution, we indicate a list of research opportunities in the scope of preprocessing combined with visualization and Visual Analytics to stimulate a shift to visual preprocessing.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/14738716211021591","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49422950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

CoSEP: A compound spring embedder layout algorithm with support for ports CoSEP：一种支持端口的复合弹簧嵌入器布局算法

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-07-01 DOI: 10.1177/14738716211028136

Alihan Okka, U. Dogrusoz, Hasan Balci

引用次数: 2

Data and visual displays in the Journal of Ecology 1996–2016 1996-2016年《生态学杂志》上的数据和视觉显示

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-01-01 DOI: 10.1177/1473871620980121

A. Friedman

{"title":"Data and visual displays in the Journal of Ecology 1996–2016","authors":"A. Friedman","doi":"10.1177/1473871620980121","DOIUrl":"https://doi.org/10.1177/1473871620980121","url":null,"abstract":"Scholars in scientific disciplines face unique challenges in the creation of visualizations, especially in publications that require insights derived from analyses to be visually displayed. The literature on visualizations describes different techniques and best practices for the creation of graphs. However, these techniques have not been used to evaluate the impact of visualizations in academic publications. In the field of ecology, as in other scientific fields, graphs are an essential part of journal articles. Little is known about the connections between the kind of data presented and domain in which the researchers conducted their study that together produces the visual graphics. This study focused on articles published in the Journal of Ecology between 1996 and 2016 to explore possible connections between data type, domain, and visualization type. Specifically, this study asked three questions: How many of the graphics published between 1996 and 2016 follow a particular set of recommendations for best practices? What can Pearson correlations reveal about the relationships between type of data, domain of study, and visual displays? Can the findings be examined through an inter-reliability test lens? Out of the 20,080 visualizations assessed, 54% included unnecessary graphical elements in the early part of the study (1996–2010). The most common type of data was univariate (35%) and it was often displayed using line graphs. Twenty-one percent of the articles in the period studied could be categorized under the domain type “single species.” Pearson correlation analysis showed that data type and domain type was positively correlated (r = 0.08; p ≤ 0.05). Cohen’s kappa for the reliability test was 0.86, suggesting good agreement between the two categories. This study provides evidence that data type and domain types are equally important in determining the type of visualizations found in scientific journals.","PeriodicalId":50360,"journal":{"name":"Information Visualization","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1473871620980121","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43246860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Images, Narrative, and Gestures for Explanation 图像，叙述和手势解释

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-01-01 DOI: 10.1016/B978-0-12-381464-7.00009-0

C. Ware

引用次数: 1

Color 颜色

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-01-01 DOI: 10.1016/b978-0-12-812875-6.00004-9

C. Ware

引用次数: 0

Space Perception 空间感知

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-01-01 DOI: 10.1016/b978-0-12-812875-6.00007-4

C. Ware

引用次数: 0

Visual Objects and Data Objects 可视化对象和数据对象

IF 2.3 4区计算机科学

Information Visualization Pub Date : 2021-01-01 DOI: 10.1016/B978-0-12-381464-7.00008-9

C. Ware

引用次数: 0