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Highlighting the Importance of Intentional Aspects in data Narrative Crafting Processes

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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Uncovering Patterns in Design Spaces: An exploration Tool for the analysis of Faceted Interface Collections 24

Uncovering Patterns in Design Spaces: An Exploration Tool fo...

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17th International conference on Advanced visual Interfaces (AVI)

作者： Keck, Mandy Freller, Lisa-Maria Neumayr, Thomas Augstein, Mirjam Univ Appl Sci Upper Austria Hagenberg Campus Hagenberg Austria

ISBN: (纸本)9798400717642

Design spaces are powerful conceptual frameworks for analyzing solutions within a problem domain. We provide an exploration and analysis tool to examine the underlying data collection, compare different solutions and analyze commonly used building blocks. The web-based tool is based on javascript and *** and is avaibable online at: https://***

关键词： Design Space Faceted Browser analysis Tool Building Blocks

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visual Explanation for Open-Domain Question Answering With BERT

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2024年第7期30卷 3779-3797页

作者： Shao, Zekai Sun, Shuran Zhao, Yuheng Wang, Siyuan Wei, Zhongyu Gui, Tao Turkay, Cagatay Chen, Siming Fudan Univ Shanghai 200437 Peoples R China Univ Warwick Coventry CV4 7AL England

Open-domain question answering (OpenQA) is an essential but challenging task in natural language processing that aims to answer questions in natural language formats on the basis of large-scale unstructured passages. Recent research has taken the performance of benchmark datasets to new heights, especially when these datasets are combined with techniques for machine reading comprehension based on Transformer models. However, as identified through our ongoing collaboration with domain experts and our review of literature, three key challenges limit their further improvement: (i) complex data with multiple long texts, (ii) complex model architecture with multiple modules, and (iii) semantically complex decision process. In this paper, we present VEQA, a visual analytics system that helps experts understand the decision reasons of OpenQA and provides insights into model improvement. The system summarizes the data flow within and between modules in the OpenQA model as the decision process takes place at the summary, instance and candidate levels. Specifically, it guides users through a summary visualization of dataset and module response to explore individual instances with a ranking visualization that incorporates context. Furthermore, VEQA supports fine-grained exploration of the decision flow within a single module through a comparative tree visualization. We demonstrate the effectiveness of VEQA in promoting interpretability and providing insights into model enhancement through a case study and expert evaluation.

关键词： Analytical models Transformers Task analysis data models visual analytics Bit error rate Semantics Explainable machine learning open-domain question answering visual analytics

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visual analysis of Spinels with General Line Coordinates 28

Visual Analysis of Spinels with General Line Coordinates

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28th International conference on Information visualisation (IV)

作者： Luque, Leandro Lujan Ganuza, Maria Bjerg, Ernesto Kovalerchuk, Boris UNS Inst Comp Sci & Engn Dept Comp Sci & Engn CONICET Bahia Blanca Argentina UNS INGEOSUR CONICET Dept Geol Bahia Blanca Argentina Cent Washington Univ Dept Comp Sci Ellensburg WA USA

ISBN: (纸本)9798350380170;9798350380163

In the geological context, the analysis of multidimensional data is a very common task and requires visualization techniques for exploration. General Line Coordinates (GLC) is a technique especially intended for lossless representation among the various techniques available for the visualization of multidimensional data. In this study, the application of GLC for pattern analysis and identification in mineral datasets is investigated. Furthermore, we develop a web-based tool to explore the possibility of employing GLC to leverage these approaches to derive visual discovery rules for pattern recognition.

关键词： General Line Coordinates Multidimensional data Geochemical data

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DoodleTunes: Interactive visual analysis of Music-Inspired Children Doodles with Automated Feature Annotation 24

DoodleTunes: Interactive Visual Analysis of Music-Inspired C...

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CHI conference on Human Factors in Computing Sytems (CHI)

作者： Liu, Shuqi Bu, Jia Ye, Huayuan Chen, Juntong Jiang, Shiqi Tao, Mingtian Guo, Liping Wang, Changbo Li, Chenhui East China Normal Univ Sch Comp Sci & Technol Shanghai Peoples R China East China Normal Univ Fac Educ Shanghai Peoples R China

ISBN: (纸本)9798400703300

Music and visual arts are essential in children's arts education, and their integration has garnered signifcant attention. Existing data analysis methods for exploring audio-visual correlations are limited. Yet, relevant research is necessary for innovating and promoting arts integration courses. In our work, we collected substantial volumes of music-inspired doodles created by children and interviewed education experts to comprehend the challenges they encountered in the relevant analysis. Based on the insights we obtained, we designed and constructed an interactive visualization system DoodleTunes. DoodleTunes integrates deep learning-driven methods for automatically annotating several types of data features. The visual designs of the system are based on a four-level analysis structure to construct a progressive workfow, facilitating data exploration and insight discovery between doodle images and corresponding music pieces. We evaluated the accuracy of our feature prediction results and collected usage feedback on DoodleTunes from fve domain experts.

关键词： Multimodal data visualization data annotation user interface audio data visual analysis painting

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Enabling Tabular data exploration for Blind and Low-Vision Users

Enabling Tabular Data Exploration for Blind and Low-Vision U...

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2024 ACM Designing Interactive Systems conference, DIS 2024

作者： Wang, Yanan Srinivasan, Arjun Kim, Yea-Seul Department of Computer Sciences University of Wisconsin-Madison MadisonWI United States Databricks Inc. SeattleWA United States

ISBN: (纸本)9798400705830

In a data-driven society, being able to examine data on one’s own terms is crucial for various aspects of well-being. However, current data exploration paradigms, such as Exploratory data analysis (EDA), heavily rely on visualizations to unveil patterns and insights. This visual-centric approach poses signifcant challenges for blind and low-vision (BLV) individuals. To address this gap, we built a prototype that supports non-visual data exploration and conducted an observational user study involving 18 BLV participants. Participants were asked to conduct various analytical tasks, as well as free exploration of provided datasets. The study fndings provide insights into the factors infuencing inefcient data exploration and characterizations of BLV participants’ analytical behaviors. We conclude by highlighting future avenues of research for the design of data exploration tools for BLV users. © 2024 Copyright held by the owner/author(s).

关键词： Human engineering

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Dash: A Bimodal data exploration Tool for Interactive Text and visualizations

Dash: A Bimodal Data Exploration Tool for Interactive Text a...

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2024 IEEE visualization and visual Analytics conference, VIS 2024

作者： Bromley, Dennis Setlur, Vidya Tableau Research United States

ISBN: (纸本)9798350354850

Integrating textual content, such as titles, annotations, and captions, with visualizations facilitates comprehension and takeaways during data exploration. Yet current tools often lack mechanisms for integrating meaningful long-form prose with visual data. This paper introduces DASH, a bimodal data exploration tool that supports integrating semantic levels into the interactive process of visualization and text-based analysis. DASH operationalizes a modified version of Lundgard et al.'s semantic hierarchy model that catego-rizes data descriptions into four levels ranging from basic encodings to high-level insights. By leveraging this structured semantic level framework and a large language model's text generation capabilities, DASH enables the creation of data-driven narratives via drag-and-drop user interaction. Through a preliminary user evaluation, we discuss the utility of DASH's text and chart integration capabilities when participants perform data exploration with the tool. © 2024 IEEE.

关键词： Spatio-temporal data

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A Personalized AI Assistant For Intuition-Driven visual explorations 20

A Personalized AI Assistant For Intuition-Driven Visual Expl...

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20th IEEE International conference on E-Science (E-Science)

作者： Hammer, James Hobson, Tanner Pugmire, David Klasky, Scott Moreland, Kenneth Huang, Jian Univ Tennessee Dept EECS Knoxville TN USA Oak Ridge Natl Lab CSMD Div Oak Ridge TN USA

ISBN: (纸本)9798350365627;9798350365610

Understanding the time-varying magnetic field within a fusion device is critical for the successful design and construction of clean-burning fusion power plants. Poincare analysis provides a powerful method for the analysis and visualization of magnetic field lines in fusion devices. Current state-of-the-art relies on manually and iteratively generating Poincare plots from simulation data. Using Poincare plots in deep analysis is very time consuming because Poincare plots can be very computationally expensive, especially for a time-varying simulation with thousands of time steps. Further, the visualization results are so complex that only expert users know how to explore, interpret, and control. In addition, collaboration is hampered due to the high barrier to entry. To this end, we contribute Fugent, a reinforcement learning-based agent capable of recommending and evaluating the importance of exploration regions based on training data captured from historic expert user usage. Using Fugent, we show that important regions can be identified and recommended for further exploration. Fugent is open source.

关键词： visual exploration Reinforcement Learning Recommendation System

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Network Narratives: data Tours for visual Network exploration and analysis 23

Network Narratives: Data Tours for Visual Network Exploratio...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Li, Wenchao Schottler, Sarah Scott-Brown, James Wang, Yun Chen, Siming Qu, Huamin Bach, Benjamin Hong Kong Univ Sci & Technol Hong Kong Peoples R China Univ Edinburgh Edinburgh Midlothian Scotland Microsoft Res Asia Beijing Peoples R China Fudan Univ Shanghai Peoples R China

ISBN: (纸本)9781450394215

This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community exploration, and other tasks. Based on interviews with five network analysts, we developed a user interface (NetworkNarratives) and 10 example tours. The interface allows analysts to navigate an interactive slideshow featuring facts about the network using visualizations and textual annotations. On each slide, an analyst can freely explore the network and specify nodes, links, or subgraphs as seed elements for follow-up tours. Two studies, comprising eight expert and 14 novice analysts, show that data tours reduce exploration effort, support learning about network exploration, and can aid the dissemination of analysis results. NetworkNarratives is available online, together with detailed illustrations for each tour.

关键词： Guided exploration network visualization

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Democratizing co-production of thematic co-explorations for Citizen Observatories 9

Democratizing co-production of thematic co-explorations for ...

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9th International conference on Smart and Sustainable Technologies (SpliTech)

作者： Lopez-de-Ipina, Diego Sanchez-Corcuera, Ruben Eduardo Vergara, Felipe Emaldi, Mikel Wolosiuk, Dawid Casado-Mansilla, Diego Feliciotti, Alessandra Peters-Anders, Jan Univ Deusto Fac Engn Bilbao Spain Univ Deusto DeustoTech Bilbao Spain VRVis Forsch GmbH Visual Analyt Grp Vienna Austria MindEarth Biel Switzerland AIT Austrian Inst Technol GmbH Vienna Austria

ISBN: (纸本)9798350390797;9789532901351

Citizen Observatories are a promising instrument to drive societal behaviour change towards greener more sustainable practices. However, assembling Citizen Observatories is not easy, since apart from the continuous engagement of their participants, there is the need to have some specialized domain and technical knowledge. data quality, continuous engagement and retention and factual impact into decision making are three usual roadblocks which impend a wider adoption of this practice. This paper explains how GREENGAGE project aims to democratize the co-production of thematic co-explorations and overcome those barriers.

关键词： Citizen Observatory thematic co-exploration co-production data analysis Green Deal

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