CAREER: Reverse Data Management: Reverse-Engineering Data Transformations to Understand, Diagnose, and Manipulate Data

职业：逆向数据管理：逆向工程数据转换以理解、诊断和操作数据

• 批准号: 1453543
• 负责人: Alexandra Meliou
• 金额: $ 55万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1453543&HistoricalAwards=false
• 关键词: CAREER; Reverse; Data; Management; Engineering

Today, data is critical in almost every aspect of society, including healthcare, education, economy, and science. Applications in these domains have benefited from the rapid growth and increased availability of data through online repositories, marketplaces, and other sharing platforms. However, because data is easily shared and reused, it has become less curated and less reliable. Data is often misused because its validity and origin are unclear, and mistakes easily propagate as data is often used to derive other data. This project will design and develop new technologies to assist data-reliant applications in overcoming these challenges, by extending data management capabilities to support operations that reverse-engineer data transformations. Understanding and reasoning with data derivations will lead to better understanding of surprising observations, more accurate and efficient diagnoses of problems, and better tools for making data-driven decisions and planning. This work will broadly impact society through the development of new data analysis capabilities, which will, in turn, improve data quality and positively affect data-driven processes. Overall, these improvements will increase the positive impact that data and computing systems have on society.This project will establish the theoretical foundations and will address practical challenges to support reverse data management capabilities in database systems. Reverse data management focuses on reverse transformations that manipulate input data on behalf of desired outcomes in the output data (as opposed to traditional data management that typically focuses on forward-moving data flows, such as querying, aggregation, and indexing). The research goal of this project is to augment database systems with user-facing reverse data management functionality. This project will target three reverse data management needs of modern applications: (1) assisting users with understanding data and verifying data-based computation results, (2) diagnosing problems by tracing the root causes of data errors, and (3) identifying changes in data and processes that lead to improved, more desirable results.For further information see the project web site at: http://rdm.cs.umass.edu

如今，数据几乎在社会的各个方面都至关重要，包括医疗保健、教育、经济和科学。这些领域的应用程序得益于快速增长和通过在线存储库、市场和其他共享平台增加的数据可用性。然而，由于数据很容易共享和重用，它变得更不可靠。数据经常被误用，因为它的有效性和来源不清楚，而且错误很容易传播，因为数据经常被用来推导其他数据。该项目将设计和开发新技术，通过扩展数据管理功能来支持逆向工程数据转换的操作，帮助依赖数据的应用程序克服这些挑战。通过数据衍生的理解和推理将更好地理解令人惊讶的观察结果，更准确、更有效地诊断问题，并为做出数据驱动的决策和规划提供更好的工具。这项工作将通过开发新的数据分析能力，对社会产生广泛的影响，进而提高数据质量，并对数据驱动的过程产生积极影响。总的来说，这些改进将增加数据和计算系统对社会的积极影响。该项目将建立理论基础，并解决实际挑战，以支持数据库系统中的反向数据管理能力。反向数据管理侧重于反向转换，这种转换代表输出数据中的期望结果来操作输入数据（与传统数据管理相反，传统数据管理通常侧重于向前移动的数据流，例如查询、聚合和索引）。这个项目的研究目标是用面向用户的反向数据管理功能来增强数据库系统。该项目将针对现代应用的三个反向数据管理需求：(1)协助用户理解数据并验证基于数据的计算结果；(2)通过追踪数据错误的根本原因来诊断问题；(3)识别数据和流程的变化，从而导致改进的、更理想的结果。欲了解更多信息，请参阅该项目的网站：http://rdm.cs.umass.edu

项目成果

EXstream: Explaining Anomalies in Event Stream Monitoring

• DOI: 10.5441/002/edbt.2017.15
• 发表时间: 2017
• 期刊: 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)
• 作者: Haopeng Zhang;Y. Diao;A. Meliou

CoCo: Interactive Exploration of Conformance Constraints for Data Understanding and Data Cleaning

CoCo：数据理解和数据清理的一致性约束的交互式探索

• DOI: 10.1145/3448016.3452750
• 发表时间: 2021
• 期刊: International Conference on Management of Data (SIGMOD
• 作者: Fariha, Anna;Tiwari, Ashish;Meliou, Alexandra;Radhakrishna, Arjun;Gulwani, Sumit
• 通讯作者: Gulwani, Sumit

Themis: Automatically testing software for discrimination

Themis：自动测试软件的歧视性

• DOI: 10.1145/3236024.3264590
• 发表时间: 2018
• 期刊: Proceedings of the Demonstrations Track at the 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE
• 作者: Angell, Rico;Johnson, Brittany;Brun, Yuriy;Meliou, Alexandra
• 通讯作者: Meliou, Alexandra

Stochastic Package Queries in Probabilistic Databases

• DOI: 10.1145/3318464.3389765
• 发表时间: 2020-05
• 期刊: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
• 作者: Matteo Brucato;Nishant Yadav;A. Abouzied;P. Haas;A. Meliou

Causality-Guided Adaptive Interventional Debugging

• DOI: 10.1145/3318464.3389694
• 发表时间: 2020-03
• 期刊: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
• 作者: Anna Fariha;Suman Nath;A. Meliou