A Question-Oriented Visualization Recommendation Approach for Data Exploration

R. A. D. Lima, Simone Diniz Junqueira Barbosa
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引用次数: 2

Abstract

The increasingly rapid growth of data production and the consequent need to explore data to obtain answers to the most varied questions have promoted the development of tools to facilitate the manipulation and construction of data visualizations. However, building useful data visualizations is not a trivial task: it may involve a large number of subtle decisions from experienced designers. In this paper, we present an approach that uses a set of heuristics to recommend data visualizations associated with questions, in order to facilitate the understanding of the recommendations and assisting the visual exploration process. Our approach was implemented and evaluated through the VisMaker tool. We carried out two studies comparing VisMaker with Voyager 2 and analyzed some aspects of the recommendation approaches through the participants' feedbacks. As a result, we found some advantages of our approach and gathered comments to help improve the development of visualization recommender tools.
面向问题的数据探索可视化推荐方法
数据生产的日益快速增长,以及随之而来的探索数据以获得各种问题答案的需求,促进了工具的发展,以方便数据可视化的操作和构建。然而,构建有用的数据可视化并不是一项微不足道的任务:它可能涉及经验丰富的设计人员的大量微妙决策。在本文中,我们提出了一种方法,该方法使用一组启发式方法来推荐与问题相关的数据可视化,以促进对建议的理解并协助视觉探索过程。我们的方法是通过VisMaker工具实施和评估的。我们进行了两项比较VisMaker和Voyager 2的研究,并通过参与者的反馈分析了推荐方法的一些方面。因此,我们发现了我们的方法的一些优点,并收集了意见,以帮助改进可视化推荐工具的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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