Declaration, Exploration, Enhancement and Provenance: The DEEP Approach to Data Quality Management Systems

声明、探索、增强和起源：数据质量管理系统的深层方法

• 批准号: DP140103171
• 负责人: Prof Xiaofang Zhou
• 金额: $ 31.58万
• 依托单位: The University of Queensland
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP140103171
• 关键词: Declaration; Exploration; Enhancement; Provenance; DEEP

The project proposes the Declaration, Exploration, Enhancement, Provenance (DEEP) approach to data quality management. The approach adopts a whole-of-data-cycle view towards addressing complex and emerging problems in data quality management and aims to develop novel and comprehensive mechanisms to improve data quality measurement, enforcement and monitoring. Due to the application-centric nature of DEEP, the outcomes from the project are expected to increase user understanding of data characteristics, improve interpretability of information derived from large, multi-source data sets and contribute to enhancement of data literacy levels in involved user communities.

该项目提出了数据质量管理的声明、探索、增强、来源（DEEP）方法。该方法采用整个数据周期的观点来解决数据质量管理中复杂和新出现的问题，旨在开发新颖且全面的机制来改善数据质量测量、执行和监控。由于深度环境方案以应用为中心的性质，预计该项目的成果将增加用户对数据特征的了解，提高从大型多源数据集获得的信息的可解释性，并有助于提高有关用户群体的数据识字水平。