PacificVis2019将于4月23-26日在泰国曼谷召开。此次的PacificVAST2019 收录了6篇文章，在Visual Informatics VI 官网2019年3月第一期上出版。
Interactive Map Reports Summarizing Bivariate Geographic Data
概述双变量地理数据的交互式地图报告
Shahid Latif, Fabian Beck
**摘要：**双变量地图可视化采用不同的编码方式来可视化两个变量，但在不同方式的编码之间进行比较具有挑战性。与单变量可视化相比，它识别区域差异和发现地理异常值要困难得多。我们提倡使用自然语言文本来增强地图可视化并理解两个地理统计变量之间的关系（尤其针对没有经验的可视化用户）。本文提出了一种方法，从数据分析中选取有意义的发现，生成其相应的文本和可视化，并将它们集成到单一文档中。生成的报告以交互方式将可视化与文本叙述联系起来。用户可以获得附加的解释，并有能力对不同的区域进行比较。文本生成过程是灵活的，采用少量参数即可适应各种地理和上下文设置。我们通过许多应用示例展示了这种灵活性。
**关键词：**地理可视化，自然语言生成，交互式文档
iMR地址：https://vis-tools.paluno.uni-due.de/imr/
全文信息
Interactive Map Reports Summarizing Bivariate Geographic Data
Shahid Latif, Fabian Beck
Abstract: Bivariate map visualizations use different encodings to visualize two variables but comparison across multiple encodings is challenging. Compared to a univariate visualization, it is significantly harder to read regional differences and spot geographical outliers. Especially targeting inexperienced users of visualizations, we advocate the use of natural language text for augmenting map visualizations and understanding the relationship between two geo-statistical variables. We propose an approach that selects interesting findings from data analysis, generates a respective text and visualization, and integrates both into a single document. The generated reports interactively link the visualization with the textual narrative. Users can get additional explanations and have the ability to compare different regions. The text generation process is flexible and adapts to various geographical and contextual settings based on small sets of parameters. We showcase this flexibility through a number of application examples.
Keywords: Geographic visualizationNatural language generationInteractive documents
Link: https://www.sciencedirect.com/science/article/pii/S2468502X19300191
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