面向分析任务的表格数据可视化交互构建  

Tabular Data Visualization Interactive Construction for Analysis Tasks

作　　者：马楠 袁晓如[1,2,3] Ma Nan;Yuan Xiaoru(Key Laboratory of Machine Perception(Ministry of Education),Peking University,Beijing 100871;National Engineering Laboratory for Big Data Analysis and Application,Peking University,Beijing 100871;Beijing Engineering Technology Research Center of Virtual Simulation and Visualization,Beijing 100871)

机构地区：[1]北京大学机器感知与智能教育部重点实验室,北京100871 [2]北京大学大数据分析与应用技术国家工程实验室,北京100871 [3]北京市虚拟仿真与可视化工程技术研究中心,北京100871

出　　处：《计算机辅助设计与图形学学报》2020年第10期1628-1636,共9页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家重点研发计划(2016QY02D0304);国家自然科学基金面上项目(61672055).

摘　　要：用户面对多属性数据时的挑战在于选择合适的属性并创建有意义的可视化.为了快速地探索更多属性,并针对不同分析任务生成合理的可视化推荐,提出一个框架.首先定义一组可视化语言规则,描述数据转换、聚合和可视化映射的规则;然后归纳总结数据分析任务及参考可视化分析任务,生成相关可视化推荐.为了帮助用户更加灵活地探索数据,在分析中生成见解,实现了一个交互式可视分析系统,基于可视化语言和分析任务规则,根据用户指定的属性及不同分析任务推荐生成有效的可视化集合.When facing multi-dimensions data,the challenge for users is to select appropriate attributes and create insightful visualizations.In order to explore more data attributes quickly and generate reasonable visualizations recommendations for different analysis tasks,we propose a new framework.Firstly,a set of visualization grammar rules is defined,and the rules of data transformation,aggregation and visual encoding are described.Also,we summarize the data analysis tasks and reference visualization analysis tasks,and construct relevant visualization recommendations.To help users explore data more flexibly and get insights in analysis,we provide an inter-active visualization system.Based on the visualization language and analysis task rules,the system generates visualization recommendations sets effectively according to users specified attributes and different analysis tasks.

关 键 词：可视分析 可视化推荐 表格数据可视化 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]