CAREER: FIREFLY - Rich Explanations for Database Queries

CAREER: FIREFLY - 数据库查询的丰富解释

• 批准号: 1552538
• 负责人: Sudeepa Roy
• 金额: $ 55万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1552538&HistoricalAwards=false
• 关键词: CAREER; FIREFLY; Rich; Explanations; Database

With the recent popularity of Big Data, a range of people including data analysts, scientists, decision makers, and ordinary Internet users are increasingly seeking high level explanations for trends and anomalies in available datasets. Such a user typically runs queries on the datasets, computes aggregates, plots the answers on a graph, and looks for explanations for what she observes. For example, she may ask: "Why are two graphs similar or different?", "Why is a sequence of points increasing or decreasing?", "Why is there a sudden spike or dip in a graph?", and so on. Existing data analysis systems focus on large-scale statistical analytics, multi-dimensional data aggregation, interactive data exploration, and sophisticated visualization support. However, there are no tools currently available that offer semantic explanations to users. This project develops a toolkit named FIREFLY (Formal Interactive Rich Explanations On-The-Fly) that provides fast, rich, insightful explanations in response to such 'why' questions asked by users. The automatic explanations provided by this tool will help users harness Big Data more effectively, and the research findings of the project will enrich Big Data analytics techniques. Furthermore, the courses developed in conjunction with this project and the research experience that it will provide students at various levels will help train them to be future researchers. Special attention will be paid to supporting diversity in this process. This project introduces a new perspective in data analysis principled upon the notions of causality, counterfactuals, and interventions. FIREFLY aims to find synopses of properties on input tuples as explanations, such that by restricting the database to tuples that entail a different value of these synopses, the answer to the query and the observation of the user changes, thereby explaining the observation. In order to efficiently return meaningful synopses as explanations, this project will develop theory, algorithms, and optimizations along three main research directions: (1) a rich framework will be established to support meaningful explanations, large classes of database queries, and a variety of questions asked by the users, (2) an interactive tool with a graphical user interface will be built to help users run queries, ask questions, and explore the explanations returned by the tool, and (3) new techniques will be developed to handle uncertainty in the input data and in the explanations themselves.

随着大数据最近的流行，包括数据分析师、科学家、决策者和普通互联网用户在内的许多人越来越多地寻求对可用数据集中的趋势和异常现象的高级解释。这样的用户通常对数据集运行查询，计算聚合，在图表上绘制答案，并寻找对她所观察到的内容的解释。例如，她可能会问：“为什么两个图表相似或不同？”、“为什么一系列点会增加或减少？”、“为什么图表中会突然出现峰值或下降？”等等。现有的数据分析系统侧重于大规模统计分析、多维数据聚合、交互式数据探索和复杂的可视化支持。然而，目前还没有可用的工具可以为用户提供语义解释。该项目开发了一个名为 FIREFLY（Formal Interactive Rich Explanations On-The-Fly）的工具包，它可以针对用户提出的此类“为什么”问题提供快速、丰富、富有洞察力的解释。该工具提供的自动解释将帮助用户更有效地利用大数据，该项目的研究成果将丰富大数据分析技术。此外，与该项目一起开发的课程以及它将为各个级别的学生提供的研究经验将有助于将他们培养成为未来的研究人员。在此过程中将特别关注支持多样性。该项目引入了基于因果关系、反事实和干预概念的数据分析的新视角。 FIREFLY 旨在找到输入元组上的属性概要作为解释，这样通过将数据库限制为需要这些概要的不同值的元组，查询的答案和用户的观察会发生变化，从而解释观察结果。为了有效地返回有意义的概要作为解释，该项目将沿着三个主要研究方向开发理论、算法和优化：（1）将建立丰富的框架来支持有意义的解释、大类数据库查询和各种用户提出的问题，(2) 将构建具有图形用户界面的交互式工具来帮助用户运行查询、提出问题并探索该工具返回的解释，以及 (3) 将开发新技术来处理不确定性在输入数据和解释本身中。

项目成果

iQCAR: inter-Query Contention Analyzer for Data Analytics Frameworks

• DOI: 10.1145/3299869.3319904
• 发表时间: 2019-06-01
• 期刊: Proceedings of the 2019 International Conference on Management of Data
• 作者: Prajakta Kalmegh;S. Babu;Sudeepa Roy
• 通讯作者: Sudeepa Roy

iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks

iQCAR：集群计算框架的查询间争用分析器演示

• DOI: 10.1145/3183713.3193567
• 发表时间: 2018-01
• 期刊: {SIGMOD} Conference 2018
• 作者: Kalmegh, Prajakta;Lundberg, Harrison;Xu, Frederick;Babu, Shivnath;Roy, Sudeepa
• 通讯作者: Roy, Sudeepa