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  • Stable visualization of connected components in dynamic graphs
    Inf. Visualization (IF 1.325) Pub Date : 2020-11-24
    Emilio Di Giacomo; Walter Didimo; Michael Kaufmann; Giuseppe Liotta

    One of the primary goals of many systems for the visual analysis of dynamically changing networks is to maintain the stability of the drawing throughout the sequence of graph changes. We investigate the scenario where the changes are determined by a stream of events, each being either an edge addition or an edge removal. The visualization must be updated immediately after each new event is received

  • A survey of tag clouds as tools for information retrieval and content representation
    Inf. Visualization (IF 1.325) Pub Date : 2020-11-08
    Úrsula Torres Parejo; Jesús R Campaña; M Amparo Vila; Miguel Delgado

    Tag clouds are tools that have been widely used on the Internet since their conception. The main applications of these textual visualizations are information retrieval, content representation and browsing of the original text from which the tags are generated. Despite the extensive use of tag clouds, their enormous popularity and the amount of research related to different aspects of them, few studies

  • GoCrystal: A gamified visual analytics tool for analysis and visualization of atomic configurations and thermodynamic energy models
    Inf. Visualization (IF 1.325) Pub Date : 2020-07-20
    Haeyong Chung; Santhosh Nandhakumar; Gopinath Polasani Vasu; Austin Vickers; Eunseok Lee

    In this article, we present GoCrystal, a new visual analytics tool for analysis and visualization of atomic configurations and thermodynamic energy models. GoCrystal’s primary objective is to support the visual analytics tasks for finding and understanding favorable atomic patterns in a lattice using gamification. We believe the performance of visual analytics tasks can be improved by employing gamification

  • A comparative user study of visualization techniques for cluster analysis of multidimensional data sets
    Inf. Visualization (IF 1.325) Pub Date : 2020-07-04
    Elio Ventocilla; Maria Riveiro

    This article presents an empirical user study that compares eight multidimensional projection techniques for supporting the estimation of the number of clusters, k, embedded in six multidimensional data sets. The selection of the techniques was based on their intended design, or use, for visually encoding data structures, that is, neighborhood relations between data points or groups of data points

  • Documentary narrative visualization: Features and modes of documentary film in narrative visualization
    Inf. Visualization (IF 1.325) Pub Date : 2020-07-03
    Judd D Bradbury; Rosanna E Guadagno

    Documentary narrative visualization is a data visualization approach using the features of documentary film. Researchers in the field of visualization are searching for better methods of constructing narratives from data sets. In this article, we explore the structure and techniques of documentary film and how they apply to the practice of constructing narrative visualization with video. We review

  • Eccentric pie charts and an unusual pie cutting
    Inf. Visualization (IF 1.325) Pub Date : 2020-06-30
    Sándor Bozóki

    The eccentric pie chart, a generalization of the traditional pie chart is introduced. An arbitrary point is fixed within the circle, and rays are drawn from it. A sector is bounded by a pair of neighboring rays and the arc between them. Eccentric pie charts have the potential of visualizing multiple sets of data, especially for small numbers of items/features. The calculations of the area-proportional

  • Interactive visual analytics tool for multidimensional quantitative and categorical data analysis
    Inf. Visualization (IF 1.325) Pub Date : 2020-05-25
    Muhammad Laiq Ur Rahman Shahid; Vladimir Molchanov; Junaid Mir; Furqan Shaukat; Lars Linsen

    With the advances in science and technology, a rapid growth of multidimensional (multivariate) datasets is observed in different fields. Projection and visualization of such data to a lower dimensional space without losing the data structure is a challenging task. We propose an interactive visual analytics tool that is applied for the combined analysis of multidimensional numerical and categorical

  • Deep learning multidimensional projections
    Inf. Visualization (IF 1.325) Pub Date : 2020-05-18
    Mateus Espadoto; Nina Sumiko Tomita Hirata; Alexandru C Telea

    Dimensionality reduction methods, also known as projections, are often used to explore multidimensional data in machine learning, data science, and information visualization. However, several such methods, such as the well-known t-distributed stochastic neighbor embedding and its variants, are computationally expensive for large datasets, suffer from stability problems, and cannot directly handle out-of-sample

  • A survey of surveys on the use of visualization for interpreting machine learning models
    Inf. Visualization (IF 1.325) Pub Date : 2020-03-19
    Angelos Chatzimparmpas; Rafael M. Martins; Ilir Jusufi; Andreas Kerren

    Research in machine learning has become very popular in recent years, with many types of models proposed to comprehend and predict patterns and trends in data originating from different domains. As these models get more and more complex, it also becomes harder for users to assess and trust their results, since their internal operations are mostly hidden in black boxes. The interpretation of machine

  • Visualization in the preprocessing phase: Getting insights from enterprise professionals
    Inf. Visualization (IF 1.325) Pub Date : 2020-01-30
    Alessandra Maciel Paz Milani; Fernando V. Paulovich; Isabel Harb Manssour

    The current information age has increasingly required organizations to become data-driven. However, analyzing and managing raw data is still a challenging part of the data mining process. Even though we can find interview studies proposing design implications or recommendations for future visualization solutions in the data mining scope, they cover the entire workflow and do not fully focus on the

  • An empirical evaluation of three-dimensional pie charts with individually extruded sectors in a geovisualization context
    Inf. Visualization (IF 1.325) Pub Date : 2020-01-21
    Raimund Schnürer; Martin Ritzi; Arzu Çöltekin; René Sieber

    This study compares participants’ performance in extracting information from three-dimensional pie charts with individually extruded sectors in a single map frame against two-dimensional pie and bar charts in adjacent map frames. Specifically, we examine the response accuracy and response times of 181 adults who were asked to (1) identify the highest magnitude, (2) estimate a proportion, (3) perform

  • Open our visualization eyes, individualization: On Albrecht Dürer’s 1515 wood cut celestial charts
    Inf. Visualization (IF 1.325) Pub Date : 2019-12-17
    Brian J d’Auriol

    The position that visualization is an intimate part of human existence and associated with the human species is advanced in this work: visualization abounds delimited by the space of individuality across human history. Visualization involves two complementary aspects of the uniqueness deemed of individuals: individualization reflects individuals’ capabilities and personalization reflects designs that

  • Visual feature fusion and its application to support unsupervised clustering tasks
    Inf. Visualization (IF 1.325) Pub Date : 2019-12-17
    Gladys M Hilasaca; Fernando V Paulovich

    The concept of involving users in the loop of analytic workflows refers to the ability to replace heuristics with user input in machine learning and data mining tasks. For supervised tasks, user engagement generally occurs via the manipulation of training data. But for unsupervised tasks, user involvement is limited to changes in the algorithm parametrization or the input data representation, also

  • Taggle: Combining overview and details in tabular data visualizations
    Inf. Visualization (IF 1.325) Pub Date : 2019-11-18
    Katarina Furmanova; Samuel Gratzl; Holger Stitz; Thomas Zichner; Miroslava Jaresova; Alexander Lex; Marc Streit

    Most tabular data visualization techniques focus on overviews, yet many practical analysis tasks are concerned with investigating individual items of interest. At the same time, relating an item to the rest of a potentially large table is important. In this work, we present Taggle, a tabular visualization technique for exploring and presenting large and complex tables. Taggle takes an item-centric

  • State-based network similarity visualization
    Inf. Visualization (IF 1.325) Pub Date : 2019-11-04
    Sugeerth Murugesan; Kristofer Bouchard; Jesse Brown; Mariam Kiran; Dan Lurie; Bernd Hamann; Gunther H Weber

    We introduce an approach for the interactive visual analysis of weighted, dynamic networks. These networks arise in areas such as computational neuroscience, sociology, and biology. Network analysis remains challenging due to complex time-varying network behavior. For example, edges disappear/reappear, communities grow/vanish, or overall network topology changes. Our technique, TimeSum, detects the

  • Projections as visual aids for classification system design.
    Inf. Visualization (IF 1.325) Pub Date : 2018-09-29
    Paulo E Rauber,Alexandre X Falcão,Alexandru C Telea

    Dimensionality reduction is a compelling alternative for high-dimensional data visualization. This method provides insight into high-dimensional feature spaces by mapping relationships between observations (high-dimensional vectors) to low (two or three) dimensional spaces. These low-dimensional representations support tasks such as outlier and group detection based on direct visualization. Supervised

  • Graphing trillions of triangles.
    Inf. Visualization (IF 1.325) Pub Date : 2017-07-12
    Paul Burkhardt

    The increasing size of Big Data is often heralded but how data are transformed and represented is also profoundly important to knowledge discovery, and this is exemplified in Big Graph analytics. Much attention has been placed on the scale of the input graph but the product of a graph algorithm can be many times larger than the input. This is true for many graph problems, such as listing all triangles

  • Visual analysis of online social media to open up the investigation of stance phenomena.
    Inf. Visualization (IF 1.325) Pub Date : 2016-04-01
    Kostiantyn Kucher,Teri Schamp-Bjerede,Andreas Kerren,Carita Paradis,Magnus Sahlgren

    Online social media are a perfect text source for stance analysis. Stance in human communication is concerned with speaker attitudes, beliefs, feelings and opinions. Expressions of stance are associated with the speakers' view of what they are talking about and what is up for discussion and negotiation in the intersubjective exchange. Taking stance is thus crucial for the social construction of meaning

  • Difference modeling for design space exploration and comparison of three-dimensional structural simulation results
    Inf. Visualization (IF 1.325) Pub Date : 2019-08-12
    Christopher Thelin; Spencer Bunnell; John Salmon; Steve Gorrell

    Design space exploration is an important part of design in engineering fields. Recent research employs surrogate models to emulate finite element analyses across a design space, allowing rapid design space exploration. With interactive speeds, there exists a need for tools that help designers compare designs to one another. This difference model is comprised of a three-dimensional rendering of the

  • A model-driven approach to automate data visualization in big data analytics
    Inf. Visualization (IF 1.325) Pub Date : 2019-07-24
    Matteo Golfarelli; Stefano Rizzi

    In big data analytics, advanced analytic techniques operate on big datasets aimed at complementing the role of traditional OLAP for decision making. To enable companies to take benefit of these techniques despite the lack of in-house technical skills, the H2020 TOREADOR Project adopts a model-driven architecture for streamlining analysis processes, from data preparation to their visualization. In this

  • EpidVis: A visual web querying tool for animal epidemiology surveillance
    Inf. Visualization (IF 1.325) Pub Date : 2019-07-13
    Samiha Fadloun; Arnaud Sallaberry; Alizé Mercier; Elena Arsevska; Mathieu Roche; Pascal Poncelet

    The use of electronic media for the detection and monitoring of animal disease outbreaks is crucial for disease surveillance and early warning systems. Animal health specialists regularly query web pages using various formulations to obtain up-to-date news on disease outbreaks. This task, however, is often manual and time-consuming. Visualization techniques can nevertheless facilitate their web searches

  • TV-MV Analytics: A visual analytics framework to explore time-varying multivariate data
    Inf. Visualization (IF 1.325) Pub Date : 2019-07-03
    Aurea Soriano-Vargas; Bernd Hamann; Maria Cristina F de Oliveira

    We present an integrated interactive framework for the visual analysis of time-varying multivariate data sets. As part of our research, we performed in-depth studies concerning the applicability of visualization techniques to obtain valuable insights. We consolidated the considered analysis and visualization methods in one framework, called TV-MV Analytics. TV-MV Analytics effectively combines visualization

  • A contextual family tree visualization design
    Inf. Visualization (IF 1.325) Pub Date : 2019-05-17
    José Borges

    With the increase in availability of online national archives and software to manage genealogical records, genealogy studies are growing in popularity. While conducting research, genealogists communicate their findings either in written narratives or in genealogical charts. In that context, visualization methods can be very effective for promoting the understanding of the intricacies of a family tree

  • Evaluation of approaches proposed to avoid overlap of markers in visualizations based on multidimensional projection techniques
    Inf. Visualization (IF 1.325) Pub Date : 2019-05-03
    Wilson E Marcílio-Jr; Danilo M Eler; Rogério E Garcia; Ives R Venturini Pola

    Multidimensional projection techniques provide graphical representations computed based on instance similarities to enable the analysis of abstract and possibly large data sets. However, when the data set size grows these graphical representations can hardly avoid overlap among markers. To overcome this issue, while some techniques attempt to remove overlap after multidimensional projection, some projection

  • Layout placement optimization methods using repeated user interface sequence patterns for client applications
    Inf. Visualization (IF 1.325) Pub Date : 2019-02-06
    Jihye Chung; Seongjin Hong; Youngbin Kim; SJ Kang; Changhun Kim

    We propose a method for automatically optimizing the layout placement of user interfaces in commercial applications. The proposed method suggests an optimal user interface component placement layout for an application by considering behavior cost, repeated user interface sequences, and preferred placement area. We used the Apriori algorithm and a genetic algorithm efficiently to optimize user interface

  • Visualization model validation via inline replication
    Inf. Visualization (IF 1.325) Pub Date : 2019-01-25
    David Gotz; Wenyuan Wang; Annie T Chen; David Borland

    Data visualizations typically show a representation of a data set with little to no focus on the repeatability or generalizability of the displayed trends and patterns. However, insights gleaned from these visualizations are often used as the basis for decisions about future events. Visualizations of retrospective data therefore often serve as “visual predictive models.” However, this visual predictive

  • Force-directed algorithms for schematic drawings and placement: A survey
    Inf. Visualization (IF 1.325) Pub Date : 2019-01-03
    Se-Hang Cheong; Yain-Whar Si

    Force-directed algorithms have been developed over the last 50 years and used in many application fields, including information visualisation, biological network visualisation, sensor networks, routing algorithms, scheduling, and graph drawing. Our survey provides a comprehensive summary of developments and a full roadmap for state-of-the-art force-directed algorithms in schematic drawings and placement

  • VafusQ: A methodology to build visual analysis applications with data quality features
    Inf. Visualization (IF 1.325) Pub Date : 2018-12-31
    Jhon Alejandro Triana; Dirk Zeckzer; Hans Hagen; Jose Tiberio Hernandez

    The use of interactive applications to support the decision-making process is more common every day. However, a huge amount of data is required in order to make more informed decisions. Fortunately, with the arrival of new technologies there are many data sources available. This requirement of data causes heterogeneity and data quality problems. A set of data quality problems are reduced in the preprocessing

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