Database System Support for Data Visualization

数据可视化的数据库系统支持

• 批准号: RGPIN-2019-06301
• 负责人: Gryz, Jaroslaw
• 金额: $ 2.04万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=682207
• 关键词: Database; System; Support; Data; Visualization

One picture is worth a thousand words. The idea of replacing*a complex narrative with a single image may have become a cliché in journalism,*but it is an absolute requirement in data exploration. After all, one may be*able to read a thousand words, but cannot possibly look at, let alone*understand, a billion data points. Visualization offers an indispensable tool*in understanding the data. ***The*process of data visualization can be described from a high-level perspective as*consisting of two steps: processing the data, then applying one of the*visualization algorithms to it. There has been significant work done on data*visualization over the last 50 years. Interestingly, most of this work*concentrated on the second step of the visualization process. This was*understandable, as data sets were relatively small and the performance of the*visualization tools was often determined by the efficiency of the graphics*algorithms. With the advent of large data sets a radical shift in the design of*data visualization tools has to be made. Data retrieval and processing time now*dominates the performance of the visualization process, so cannot be ignored.*Without efficient database support, visualization, in particular, interactive*visualization is impossible. ***The research program we propose addresses this very problem. We*will look into different visualization techniques over different types of data*and analyze the performance of the data processing engine that pre-processes*data to be visualized. We will offer new data processing techniques to improve*the performance of the back-end system and integrate them with the front-end*visualization step. We expect to build prototypes of such systems and*demonstrate experimentally their viability.

一张图片胜过千言万语。用一张图片取代复杂的叙述可能已经成为新闻业的陈词滥调，但这是数据探索的绝对要求。毕竟，一个人可能能够阅读一千个单词，但不可能看到，更不用说理解十亿个数据点了。可视化为理解数据提供了不可或缺的工具。* 数据可视化的 * 过程可以从高层次的角度描述为 * 包括两个步骤：处理数据，然后将其中一个 * 可视化算法应用于数据。在过去的50年里，数据可视化已经做了大量的工作。有趣的是，这项工作的大部分 * 集中在可视化过程的第二步。这是可以理解的，因为数据集相对较小，可视化工具的性能通常由图形算法的效率决定。随着大数据集的出现，数据可视化工具的设计必须进行根本性的转变。数据检索和处理时间现在 * 主导了可视化过程的性能，因此不能被忽视。如果没有高效的数据库支持，可视化（特别是交互式 * 可视化）是不可能的。**我们 * 将研究不同类型数据 * 的不同可视化技术，并分析预处理 * 要可视化的数据的数据处理引擎的性能。我们将提供新的数据处理技术，以提高 * 后端系统的性能，并将其与前端 * 可视化步骤集成。我们希望构建此类系统的原型，并通过实验证明其可行性。