Building data visualization and exploration support into an embedded database system: Big Data in the small

将数据可视化和探索支持构建到嵌入式数据库系统中：小中的大数据

• 批准号: 461932-2013
• 负责人: Godfrey, Parke
• 金额: $ 3.82万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=618796
• 关键词: Building; data; visualization; exploration; support

Relational database systems have been, and in many ways continue to be, the main driving engine behind thedata revolution. The hallmarks of these systems that enabled the revolution are relative efficiency, powerful,elegant, declarative query languages, and transactional consistency.Codd's Principle of Data Independence provided for a layer of abstraction that has allowed applications andusers to deal with the data at a logical level, without need to know how the database system deals with the dataat the physical level. Data independence allows for the database engine to ensure transactional consistency; thisremoves the need for application programs to do so. This bargain has made writing a wide range of large dataapplications significantly easier.But this bargain does come with costs too, of course. One is limited to what the "query-language" interfaces,such as SQL and Xquery, provide. While SQL has evolved into a quite competent platform for relational datamanagement and for complex analytic queries backing business applications, it is, with no small irony, poorlysuited for data exploration and visualization tasks. Meanwhile, exploration and visualization of large datacollections has become just as important a need today as has been traditional data management in the past.We plan to provide a scale-free, progressive, direct visualization of aggregate data for types of SQL queriestowards supporting data exploration.

关系数据库系统一直是，并且在许多方面将继续是数据革命背后的主要驱动引擎。这些系统促成了这场革命，它们的特点是相对高效、强大、优雅、声明性查询语言和事务一致性。Codd的数据独立原则提供了一个抽象层，允许应用程序和用户在逻辑层处理数据，而不需要知道数据库系统如何在物理层处理数据。数据独立性允许数据库引擎确保事务一致性；这消除了应用程序这样做的需要。这种折衷使得编写大范围的大型数据应用程序变得非常容易。当然，这种讨价还价也有代价。一种是受限于“查询语言”接口（如SQL和Xquery）所提供的功能。虽然SQL已经发展成为关系数据管理和支持业务应用程序的复杂分析查询的一个相当有能力的平台，但具有讽刺意味的是，它不太适合数据探索和可视化任务。与此同时，对大型数据集的探索和可视化已经成为一种与过去传统数据管理同样重要的需求。我们计划为SQL查询类型的聚合数据提供无标度的、渐进的、直接的可视化，以支持数据探索。