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Asymmetric Relations in Longitudinal Social Networks

IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2011年第12期17卷 2283-2290页

作者： Brandes, Ulrik Nick, Bobo Univ Konstanz Dept Comp & Informat Sci D-7750 Constance Germany

In modeling and analysis of longitudinal social networks, visual exploration is used in particular to complement and inform other methods. The most common graphical representations for this purpose appear to be animations and small multiples of intermediate states, depending on the type of media available. We present an alternative approach based on matrix representation of gestaltlines (a combination of Tufte's sparklines with glyphs based on gestalt theory). As a result, we obtain static, compact, yet data-rich diagrams that support specifically the exploration of evolving dyadic relations and persistent group structure, although at the expense of cross-sectional network views and indirect linkages.

关键词： Network visualization Social Networks Time Series data visual Knowledge Discovery and Representation Glyph-based Techniques

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exploration of patterns predicting renal damage in patients with diabetes type ii using a visual temporal analysis laboratory

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2015年第2期22卷 275-289页

作者： Klimov, Denis Shknevsky, Alexander Shahar, Yuval Ben Gurion Univ Negev Fac Engn Sci Dept Informat Syst Engn IL-84105 Beer Sheva Israel

Objective To analyze the longitudinal data of multiple patients and to discover new temporal knowledge, we designed and developed the visual Temporal analysis Laboratory (ViTA-Lab). In this study, we demonstrate several of the capabilities of the ViTA-Lab framework through the exploration of renal-damage risk factors in patients with diabetes type ii. Materials and methods The ViTA-Lab framework combines data-driven temporal data mining techniques, with interactive, query-driven, visual analytical capabilities, to support, in an integrated fashion, an iterative investigation of time-oriented clinical data and of patterns discovered in them. Patterns discovered through the data mining mode can be explored visually, and vice versa. Both analysis modes are supported by a rich underlying ontology of clinical concepts, their relations, and their temporal properties. The knowledge enables us to apply a temporal-abstraction pre-processing phase that abstracts in a context-sensitive manner raw time-stamped data into interval-based clinically meaningful interpretations, increasing the results' significance. We demonstrate our approach through the exploration of risk factors associated with future renal damage (micro-albuminuria and macro-albuminuria) and their relationship to the hemoglobin A1C (HbA1C) and creatinine level concepts, in the longitudinal records of 22 000 patients with diabetes type ii followed for up to 5 years. Results The iterative ViTA-Lab analysis process was highly feasible. Higher ranges of either normal albuminuria or normal creatinine values and their combination were shown to be significantly associated with future micro-albuminuria and macro-albuminuria. The risk increased given high HbA1C levels for women in the lower range of normal albuminuria, and for men in the higher range of albuminuria. Conclusions The ViTA-Lab framework can potentially serve as a virtual laboratory for investigations of large masses of longitudinal clinical databases, for d

关键词： visual Analytics data analysis temporal data mining knowledge discovery temporal abstraction ontologies

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A visual Analytics Framework for Microblog data analysis at Multiple Scales of Aggregation

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COMPUTER GRAPHICS FORUM 2016年第3期35卷 441-450页

作者： Zhang, Jiawei Ahlbrand, Benjamin Malik, Abish Chae, Junghoon Min, Zhiyu Ko, Sungahn Ebert, David S. Purdue Univ W Lafayette IN 47907 USA Univ Sci & Technol China Hefei Peoples R China Ulsan Natl Inst Sci & Technol Ulsan South Korea

Real-time microblogs can be utilized to provide situational awareness during emergency and disaster events. However, the utilization of these datasets requires the decision makers to perform their exploration and analysis across a range of data scales from local to global, while maintaining a cohesive thematic context of the transition between the different granularity levels. The exploration of different information dimensions at the varied data and human scales remains to be a non-trivial task. To this end, we present a visual analytics situational awareness environment that supports the real-time exploration of microblog data across multiple scales of analysis. We classify microblogs based on a fine-grained, crisis-related categorization approach, and visualize the spatiotemporal evolution of multiple categories by coupling a spatial lens with a glyph-based visual design. We propose a transparency-based spatial context preserving technique that maintains a smooth transition between different spatial scales. To evaluate our system, we conduct user studies and provide domain expert feedback.

关键词： Categories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: visual Analytics Social Media analysis Disaster Management&mdash

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Designing for visual data exploration in Multi-Device Environments

Designing for Visual Data Exploration in Multi-Device Enviro...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Horak, Tom Tech Univ Dresden Interact Media Lab Dresden Germany

ISBN: (纸本)9781450359719

Multi-device environments have an enormous potential to enable more flexible workflows during our daily work. At the same time, visual data exploration is characterized as a fragmented sensemaking process requiring a high degree of flexibility. In my thesis, I am aiming to bring these two worlds into symbiosis, specifically for sensemaking with multivariate data visualizations and graph visualizations. This involves three main objectives: (i) understanding the devices' roles in dynamic device ensembles and their relations to exploration patterns, (ii) identifying mechanisms for adapting visualizations for different devices while preserving a consistent perception and interaction, and, finally, (iii) supporting users and developers in designing such distributed visualization interfaces, e.g., through specific guidelines. As specific contributions, it is planned that (i) and (ii) emerge into a design space, while (iii) leads to a set of heuristics. So far, I was able to extensively work on the first objective as well as to touch on the other two.

关键词： visual data analysis cross-device interaction mobile visualization

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Interactive interaction plot Supporting parameter space exploration in a design phase

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visual COMPUTER 2015年第6-8期31卷 1055-1065页

作者： Splechtna, Rainer Elshehaly, Mai Gracanin, Denis Duras, Mario Buehler, Katja Matkovic, Kresimir VRVis Res Ctr Vienna Austria Virginia Tech Ctr Human Comp Interact Blacksburg VA USA Virginia Tech Dept Comp Sci Blacksburg VA USA AVL AST Doo Zagreb Croatia

Design of experiments (DOE) is the study of how to vary control parameters to efficiently design and evaluate experiments. Main effects plot and interaction plot are two data views often used to explore differences between mean values and interactions between the DOE parameters but they are mostly limited to two parameters. We propose a new data view, interactive interaction plot, that supports exploration and analysis of high-dimensional interactions between parameters. The data view is integrated within a coordinated multiple views system. We describe the new data view using an Olympic medals data set. We also describe a case study dealing with initial selection of hybrid vehicle components. Very positive feedback from automotive domain experts demonstrates the usefulness of the newly proposed approach.

关键词： Interactive visual analysis Interaction plot Main effects plot Design of experiments

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VERTIGo: A visual Platform for Querying and Exploring Large Multilayer Networks

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2022年第3期28卷 1634-1647页

作者： Cuenca, Erick Sallaberry, Arnaud Ienco, Dino Poncelet, Pascal Yachay Tech Univ Urcuqui 100650 Ecuador Univ Montpellier Paul Valery Univ Montpellier LIRMM AMIS Res Grp F-34000 Montpellier France CNRS F-75016 Paris France INRAE F-69100 Villeurbanne France Univ Montpellier LIRMM F-34000 Montpellier France

Many real world data can be modeled by a graph with a set of nodes interconnected to each other by multiple relationships. Such a rich graph is called multilayer graph or network. Providing useful visualization tools to support the query process for such graphs is challenging. Although many approaches have addressed the visual query construction, few efforts have been done to provide a contextualized exploration of query results and suggestion strategies to refine the original query. This is due to several issues such as i) the size of the graphs ii) the large number of retrieved results and iii) the way they can be organized to facilitate their exploration. In this article, we present VERTIGo, a novel visual platform to query, explore and support the analysis of large multilayer graphs. VERTIGo provides coordinated views to navigate and explore the large set of retrieved results at different granularity levels. In addition, the proposed system supports the refinement of the query by visual suggestions to guide the user through the exploration process. Two examples and a user study demonstrate how VERTIGo can be used to perform visual analysis (query, exploration, and suggestion) on real world multilayer networks.

关键词： visualization Nonhomogeneous media Task analysis Social networking (online) Query processing databases Standards visual querying system visual pattern suggestion multilayer networks

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Voyager: Exploratory analysis via Faceted Browsing of visualization Recommendations

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2016年第1期22卷 649-658页

作者： Wongsuphasawat, Kanit Moritz, Dominik Anand, Anushka Mackinlay, Jock Howe, Bill Heer, Jeffrey Univ Washington Seattle WA 98195 USA

General visualization tools typically require manual specification of views: analysts must select data variables and then choose which transformations and visual encodings to apply. These decisions often involve both domain and visualization design expertise, and may impose a tedious specification process that impedes exploration. In this paper, we seek to complement manual chart construction with interactive navigation of a gallery of automatically-generated visualizations. We contribute Voyager, a mixed-initiative system that supports faceted browsing of recommended charts chosen according to statistical and perceptual measures. We describe Voyager's architecture, motivating design principles, and methods for generating and interacting with visualization recommendations. In a study comparing Voyager to a manual visualization specification tool, we find that Voyager facilitates exploration of previously unseen data and leads to increased data variable coverage. We then distill design implications for visualization tools, in particular the need to balance rapid exploration and targeted question-answering.

关键词： User interfaces information visualization exploratory analysis visualization recommendation mixed-initiative systems

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Engineering Annotations to Support Analytical Provenance in visual exploration Processes 22nd

Engineering Annotations to Support Analytical Provenance in ...

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22nd International conference on Web Engineering (ICWE)

作者： Tikat, Maroua Menin, Aline Buffa, Michel Winckler, Marco Univ Cote dAzur CNRS INRIA I3SSPARKS Wimm Team Nice France

ISBN: (纸本)9783031099175;9783031099168

This paper focuses on the fundamental role played by annotations to support provenance analysis in visual exploration processes of large datasets. Particularly, we investigate the use of annotations during the visual exploration of semantic datasets assisted by chained visualization techniques. In this paper, we identify three potential uses of annotations: (i) documenting findings (including errors in the dataset), (ii) supporting collaborative reasoning among teammates, and (iii) analysing provenance during the exploratory process. To demonstrate the feasibility of our approach, we implemented it as a tool support, while illustrating its usage and effectiveness through a series of use case scenarios. We identify the attributes and meta-data that describe the dependencies between annotations and visual representations, and we illustrate these dependencies through a domain-specific model.

关键词： Annotations Provenance analysis visual exploration Information visualization data quality

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From visual exploration to Storytelling and Back Again

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COMPUTER GRAPHICS FORUM 2016年第3期35卷 491-500页

作者： Gratzl, S. Lex, A. Gehlenborg, N. Cosgrove, N. Streit, M. Johannes Kepler Univ Linz Linz Austria Univ Utah Salt Lake City UT 84112 USA Harvard Med Sch Boston MA USA

The primary goal of visual data exploration tools is to enable the discovery of new insights. To justify and reproduce insights, the discovery process needs to be documented and communicated. A common approach to documenting and presenting findings is to capture visualizations as images or videos. Images, however, are insufficient for telling the story of a visual discovery, as they lack full provenance information and context. Videos are difficult to produce and edit, particularly due to the non-linear nature of the exploratory process. Most importantly, however, neither approach provides the opportunity to return to any point in the exploration in order to review the state of the visualization in detail or to conduct additional analyses. In this paper we present CLUE (Capture, Label, Understand, Explain), a model that tightly integrates data exploration and presentation of discoveries. Based on provenance data captured during the exploration process, users can extract key steps, add annotations, and author Vistories, visual stories based on the history of the exploration. These Vistories can be shared for others to view, but also to retrace and extend the original analysis. We discuss how the CLUE approach can be integrated into visualization tools and provide a prototype implementation. Finally, we demonstrate the general applicability of the model in two usage scenarios: a Gapminder-inspired visualization to explore public health data and an example from molecular biology that illustrates how Vistories could be used in scientific journals.

关键词： Categories and Subject Descriptors (according to ACM CCS): H.5.2 [Information Systems]: Information Interfaces and Presentation&mdash User Interfaces-Graphical user interfaces

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VECTOR QUANTIZATION - A TOOL FOR exploration AND analysis OF MULTIVARIATE IMAGES 2

VECTOR QUANTIZATION - A TOOL FOR EXPLORATION AND ANALYSIS OF...

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conference on visual data exploration and analysis ii

作者： SOUTHARD, DA UNIV MASSACHUSETTS DEPT COMP SCIINST VISUALIZAT & PERCEPT RESLOWELLMA 01854

ISBN: (纸本)0819417572

We discuss how vector quantization, a technique well known for data compression, can be applied to exploratory data visualization. This technique is especially useful for multivariate imagery, because it reduces the data to a manageable size, without stripping important features. Previous visualization methods are able to combine up to three variables per pixel into an integrated display. Our vector quantization technique allows us to integrate essentially any number of variables per pixel. Furthermore, the cluster analysis inherent in vector quantization has the property of identifying relationships within the data, based on similarity of textural and sample features. We use straightforward techniques to visualize these relationships interactively. The result is a tool that applies to a wide variety of imagery visualization problems. Our prototype uses contrast enhancement, color scales, and highlighting for interactive feature extraction. We show examples from panchromatic and multispectral earth observation satellites and medical imagery.

关键词： VECTOR QUANTIZATION IMAGE COMPRESSION MULTIVARIATE IMAGES EXPLORATORY visualIZATION

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