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Understanding a sequence of sequences: visual exploration of categorical states in lake sediment cores

IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2018年第1期24卷 66-76页

作者： Unger, Andrea Drager, Nadine Sips, Mike Lehmann, Dirk J. GFZ German Res Ctr Geosci Potsdam Germany Univ Magdeburg Magdeburg Germany

This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate conditions in the past. To this end, geoscientists identify which categorical sequences are similar in the sense that they indicate similar conditions. Categorical sequences are similar if they have similar meaning (semantic similarity) and appear in similar time periods (temporal similarity). For data sets with many different categorical sequences, the task to identify similar sequences becomes a challenge. Our contribution is a tailored visual analysis concept that effectively supports the analytical process. Our visual interface comprises coupled visualizations of semantics and temporal context for the exploration and assessment of the similarity of categorical sequences. Integrated automatic methods reduce the analytical effort substantially. They (1) extract unique sequences in the data and (2) rank sequences by a similarity measure during the search for similar sequences. We evaluated our concept by demonstrations of our prototype to a larger audience and hands-on analysis sessions for two different lakes. According to geoscientists, our approach fills an important methodological gap in the application domain.

关键词： visualization in Earth Science Time Series data Categorical data Design Study

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VISTILES: Coordinating and Combining Co-located Mobile Devices for visual data exploration

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2018年第1期24卷 626-636页

作者： Langner, Ricardo Horak, Tom Dachselt, Raimund Tech Univ Dresden Interact Media Lab Dresden Germany

We present VISTILES, a conceptual framework that uses a set of mobile devices to distribute and coordinate visualization views for the exploration of multivariate data. In contrast to desktop-based interfaces for information visualization, mobile devices offer the potential to provide a dynamic and user-defined interface supporting co-located collaborative data exploration with different individual workflows. As part of our framework, we contribute concepts that enable users to interact with coordinated & multiple views (CMV) that are distributed across several mobile devices. The major components of the framework are: (i) dynamic and flexible layouts for CMV focusing on the distribution of views and (ii) an interaction concept for smart adaptations and combinations of visualizations utilizing explicit side-by-side arrangements of devices. As a result, users can benefit from the possibility to combine devices and organize them in meaningful spatial layouts. Furthermore, we present a web-based prototype implementation as a specific instance of our concepts. This implementation provides a practical application case enabling users to explore a multivariate data collection. We also illustrate the design process including feedback from a preliminary user study, which informed the design of both the concepts and the final prototype.

关键词： Mobile devices coordinated & multiple views multi-display environment cross-device interaction

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visual analysis of Spatio-temporal Phenomena with 1D Projections

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COMPUTER GRAPHICS FORUM 2021年第3期40卷 335-347页

作者： Franke, M. Martin, H. Koch, S. Kurzhals, K. Univ Stuttgart Stuttgart Germany Swiss Fed Inst Technol Zurich Switzerland Inst Adv Res Artificial Intelligence Vienna Austria

It is crucial to visually extrapolate the characteristics of their evolution to understand critical spatio-temporal events such as earthquakes, fires, or the spreading of a disease. Animations embedded in the spatial context can be helpful for understanding details, but have proven to be less effective for overview and comparison tasks. We present an interactive approach for the exploration of spatio-temporal data, based on a set of neighborhood-preserving 1D projections which help identify patterns and support the comparison of numerous time steps and multivariate data. An important objective of the proposed approach is the visual description of local neighborhoods in the 1D projection to reveal patterns of similarity and propagation. As this locality cannot generally be guaranteed, we provide a selection of different projection techniques, as well as a hierarchical approach, to support the analysis of different data characteristics. In addition, we offer an interactive exploration technique to reorganize and improve the mapping locally to users' foci of interest. We demonstrate the usefulness of our approach with different real-world application scenarios and discuss the feedback we received from domain and visualization experts.

关键词： CCS Concepts • Human-centered computing → visual analytics Geographic visualization Information visualization visualization systems and tools

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Highlighting the Importance of Intentional Aspects in data Narrative Crafting Processes

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INFORMATION SYSTEMS FRONTIERS 2024年第5期26卷 1785-1801页

作者： El Outa, Faten Marcel, Patrick Peralta, Veronika Vassiliadis, Panos Univ Tours Blois France Univ Tours Comp Sci Dept Blois France Univ Ioannina Ioannina Greece

data narration is the activity of crafting narratives supported by facts extracted from data exploration and analysis, using interactive visualizations. While data narration has recently attracted much attention, the process of crafting data narratives is loosely documented and has not yet been formally described. In this article, we propose a comprehensive and well-founded process to fill this need. It aims at (i) supporting the complete cycle of data narration, from the exploration of data to the visual rendering of the narrative, (ii) being flexible enough to cover a wide range of crafting practices, and (iii) being well founded upon a conceptual model of the domain. In addition, we investigate several crafting scenarios that represent typical situations and detail the workflow of one particular phase, which reflects the intentional aspects.

关键词： data narrative crafting data journalism Process

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Patterns and Sequences: Interactive exploration of Clickstreams to Understand Common Visitor Paths

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2017年第1期23卷 321-330页

作者： Liu, Zhicheng Wang, Yang Dontcheva, Mira Hoffman, Matthew Walker, Seth Wilson, Alan Adobe Res San Jose CA USA Univ Calif Davis Davis CA USA Adobe Syst Inc San Jose CA USA

Modern web clickstream data consists of long, high-dimensional sequences of multivariate events, making it difficult to analyze. Following the overarching principle that the visual interface should provide information about the dataset at multiple levels of granularity and allow users to easily navigate across these levels, we identify four levels of granularity in clickstream analysis: patterns, segments, sequences and events. We present an analytic pipeline consisting of three stages: pattern mining, pattern pruning and coordinated exploration between patterns and sequences. Based on this approach, we discuss properties of maximal sequential patterns, propose methods to reduce the number of patterns and describe design considerations for visualizing the extracted sequential patterns and the corresponding raw sequences. We demonstrate the viability of our approach through an analysis scenario and discuss the strengths and limitations of the methods based on user feedback.

关键词： Clickstream data sequence mining visual analytics event sequences

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visualization and analysis of Rotating Stall for Transonic Jet Engine Simulation

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2016年第1期22卷 847-856页

作者： Chen, Chun-Ming Dutta, Soumya Liu, Xiaotong Heinlein, Gregory Shen, Han-Wei Chen, Jen-Ping Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA Ohio State Univ Dept Mech & Aerosp Engn Columbus OH 43210 USA

Identification of early signs of rotating stall is essential for the study of turbine engine stability. With recent advancements of high performance computing. high-resolution unsteady flow fields allow in depth exploration of rotating stall and its possible causes. Performing stall analysis, however, involves significant effort to process large amounts of simulation data, especially when investigating abnormalities across many time steps. In order to assist scientists during the exploration process, we present a visual analytics framework to identify suspected spatiotemporal regions through a comparative visualization so that scientists are able to focus on relevant data in more detail. To achieve this, we propose efficient stall analysis algorithms derived from domain knowledge and convey the analysis results through juxtaposed interactive plots. Using our integrated visualization system, scientists can visually investigate the detected regions for potential stall initiation and further explore these regions to enhance the understanding of this phenomenon. Positive feedback from scientists demonstrate the efficacy of our system in analyzing rotating stall.

关键词： Turbine flow visualization vortex extraction anomaly detection juxtaposition brushing and linking time series

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Packed-Memory Quadtree: A cache-oblivious data structure for visual exploration of streaming spatiotemporal big data

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COMPUTERS & GRAPHICS-UK 2018年 76卷 117-128页

作者： Toss, Julio Pahins, Cicero A. L. Raffin, Bruno Comba, Joao L. D. Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil Univ Grenoble Alpes Inria CNRS Grenoble INPLIG F-38000 Grenoble France

The visual analysis of large multidimensional spatiotemporal datasets poses challenging questions regarding storage requirements and query performance. Several data structures have recently been proposed to address these problems that rely on indexes that pre-compute different aggregations from a known-a-priori dataset. Consider now the problem of handling streaming datasets, in which data arrive as one or more continuous data streams. Such datasets introduce challenges to the data structure, which now has to support dynamic updates (insertions/deletions) and rebalancing operations to perform self reorganizations. In this work, we present the Packed-Memory Quadtree (PMQ), a novel data structure designed to support visual exploration of streaming spatiotemporal datasets. PMQ is cache-oblivious to perform well under different cache configurations. We store streaming data in an internal index that keeps a spatiotemporal ordering over the data following a quadtree representation, with support for real-time insertions and deletions. We validate our data structure under different dynamic scenarios and compare to competing strategies. We demonstrate how PMQ could be used to answer different types of visual spatiotemporal range queries of streaming datasets. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Spatiotemporal datasets Streaming Real-time exploration Range queries

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NOVEL APPROACH TO INTERACTIVE EDITING OF RASTER BASED data 2

NOVEL APPROACH TO INTERACTIVE EDITING OF RASTER BASED DATA

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conference on visual data exploration and analysis ii

作者： LUI, AK BONE, D AUSTRALIAN NATL UNIV CSIROCOMP SCI LABDIV INFORMAT TECHNOLCANBERRAACT 2600AUSTRALIA

ISBN: (纸本)0819417572

Expert interpretation of raster-based data, needed when, for example, automatic reconstruction of sparsely sampled data cannot produce accurate models, requires a means for interaction through which the expert's knowledge can be incorporated into the model to improve accuracy. If such expert interpretation is to be viable, the interaction must be intuitive, direct and flexible. We present a novel approach to the design of such interaction: the use of the discrete thin-plate spline permits interactive manipulation of the stiffness and tension parameters in the plate to control the behavior between control points; an object based approach allows raster based objects to be manipulated in an intuitive manner in the context of a visual representation of the objects. The editor adopts a problem driven approach which allows specialized editing tools to be developed for editing in a specific application domain. A prototype implementation of the editor is presented which provides insights into the advantages and limitations of the approach.

关键词： COMPUTER GRAPHICS HUMAN-COMPUTER INTERACTION RASTER BASED data EDITING THIN-PLATE SPLINES INTERACTIVE EDITING DIRECT MANIPULATION OBJECT BASED EDITING visualIZATION OBJECT COMPOSITION

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SparQs: visual Analytics for Sparking Creativity in Social Media exploration 9th

SparQs: Visual Analytics for Sparking Creativity in Social M...

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9th International conference on Social Computing and Social Media (SCSM) Held as Part of 19th International conference on Human-Computer Interaction (HCI International)

作者： Chen, Nan-Chen Brooks, Michael Kocielnik, Rafal Hong, Sungsoo (Ray) Smith, Jeff Lin, Sanny Qu, Zening Aragon, Cecilia Univ Washington Seattle WA 98195 USA

ISBN: (纸本)9783319585628;9783319585611

Social media has become a fruitful platform on which to study human behavior and social phenomena. However, social media data are usually messy, disorganized, and noisy, which makes finding patterns in such data a challenging task. visualization can help with the exploration of such massive data. Researchers studying social media often begin by reviewing related research. In this paper, we consider the idea that information from related research can be incorporated into social media visualization tools in order to spark creativity and guide exploration. To develop an effective overview of social media research with which to seed our tool, we conducted a content analysis of social media related papers and designed SparQs, a visual analytics tool to spark creativity in social media exploration. We conducted a pilot evaluation with three social media researchers as well as a participatory design workshop to explore further directions.

关键词： visualization visual analytics Social media Exploratory analysis Research questions Social science

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TransGraph: Hierarchical exploration of Transition Relationships in Time-Varying Volumetric data

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2011年第12期17卷 2015-2024页

作者： Gu, Yi Wang, Chaoli Michigan Technol Univ Dept Comp Sci Houghton MI 49931 USA

A fundamental challenge for time-varying volume data analysis and visualization is the lack of capability to observe and track data change or evolution in an occlusion-free, controllable, and adaptive fashion. In this paper, we propose to organize a time-varying data set into a hierarchy of states. By deriving transition probabilities among states, we construct a global map that captures the essential transition relationships in the time-varying data. We introduce the TransGraph, a graph-based representation to visualize hierarchical state transition relationships. The TransGraph not only provides a visual mapping that abstracts data evolution over time in different levels of detail, but also serves as a navigation tool that guides data exploration and tracking. The user interacts with the TransGraph and makes connection to the volumetric data through brushing and linking. A set of intuitive queries is provided to enable knowledge extraction from time-varying data. We test our approach with time-varying data sets of different characteristics and the results show that the TransGraph can effectively augment our ability in understanding time-varying data.

关键词： Time-varying data visualization hierarchical representation states transition relationship user interface

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