Literature DB >> 31425110

DataShot: Automatic Generation of Fact Sheets from Tabular Data.

Yun Wang, Zhida Sun, Haidong Zhang, Weiwei Cui, Ke Xu, Xiaojuan Ma, Dongmei Zhang.   

Abstract

Fact sheets with vivid graphical design and intriguing statistical insights are prevalent for presenting raw data. They help audiences understand data-related facts effectively and make a deep impression. However, designing a fact sheet requires both data and design expertise and is a laborious and time-consuming process. One needs to not only understand the data in depth but also produce intricate graphical representations. To assist in the design process, we present DataShot which, to the best of our knowledge, is the first automated system that creates fact sheets automatically from tabular data. First, we conduct a qualitative analysis of 245 infographic examples to explore general infographic design space at both the sheet and element levels. We identify common infographic structures, sheet layouts, fact types, and visualization styles during the study. Based on these findings, we propose a fact sheet generation pipeline, consisting of fact extraction, fact composition, and presentation synthesis, for the auto-generation workflow. To validate our system, we present use cases with three real-world datasets. We conduct an in-lab user study to understand the usage of our system. Our evaluation results show that DataShot can efficiently generate satisfactory fact sheets to support further customization and data presentation.

Year:  2019        PMID: 31425110     DOI: 10.1109/TVCG.2019.2934398

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  2 in total

Review 1.  Designing Infographics: Visual Representations for Enhancing Education, Communication, and Scientific Research.

Authors:  Lisa Traboco; Haridha Pandian; Elena Nikiphorou; Latika Gupta
Journal:  J Korean Med Sci       Date:  2022-07-11       Impact factor: 5.354

2.  Visual Data Analysis with Task-Based Recommendations.

Authors:  Leixian Shen; Enya Shen; Zhiwei Tai; Yihao Xu; Jiaxiang Dong; Jianmin Wang
Journal:  Data Sci Eng       Date:  2022-09-13
  2 in total

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