III: Small: Collaborative Research: Curation And Integration Of Inconsistent And Incomplete Temporal Data

III：小：协作研究：不一致和不完整的时态数据的管理和整合

• 批准号: 1524469
• 负责人: Jan Chomicki
• 金额: $ 25万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1524469&HistoricalAwards=false
• 关键词: III; Small; Collaborative; Research; Curation

In today's digital world, incomplete and inconsistent information about an entity can often be found in multiple different data sources, or in different versions of the same source at different times. To harness the rich amount of information available, many organizations curate and integrate public (and private) data over time to create a comprehensive temporal view of relevant entities. This project will have the potential to make significant societal impact through the development of a software prototype for data curation and integration. Such a prototype will enable the users to construct robust, application-specific, consistent views of temporal data on demand, which will lead to new classes of applications, particularly those involving profiling, tracking, monitoring, archiving and understanding of the evolution of entities over time. This project will also provide the opportunity to train students in several critical research areas central to temporal databases, data analytics and big data. The results obtained in this investigation will be incorporated into advanced graduate courses on large-scale data integration offered at both SUNY at Buffalo and UC Santa Cruz. The software artifacts and datasets produced will be made freely available for broad dissemination and sharing.This project will advance the state-of-the-art in data curation and integration over temporal data through addressing three fundamental challenges. First, unlike incompleteness in non-temporal data, incompleteness in temporal data may be time-varying. Time-varying incompleteness will necessitate the introduction of time-dependent nulls. The second challenge is that inconsistency can also occur in temporal data. Inconsistency will be handled by declaratively specifying temporal preferences and algorithms to resolve conflicts based on those preferences. Alternatively, under the assumption that the inconsistent temporal database is left as is, this project will consider how consistent query answers can be computed over such a database. This project will also consider, for the first time, data with both incompleteness and inconsistency in a single formal framework, which will require significant conceptual and practical advances. The third challenge is to achieve temporal data independence through a conceptual framework that will use a formal, two-tier approach to manage temporal data; the abstract view provides the semantics and the concrete view for the physical representation of temporal data. The views hide lower-level details and allow for declarative, logical specification of queries, mappings, and dependencies. For further information see the project web site at http://greenwich.sites.ucsc.edu or http://www.cse.buffalo.edu/~chomicki/.

在当今的数字世界中，关于一个实体的不完整和不一致的信息经常可以在多个不同的数据源中找到，或者在同一个源的不同版本中在不同的时间发现。为了利用丰富的可用信息，许多组织随着时间的推移管理和集成公共(和私有)数据，以创建相关实体的全面时间视图。该项目将有可能通过开发用于数据管理和整合的软件原型产生重大的社会影响。这样的原型将使用户能够根据需要构建强大的、特定于应用程序的、一致的时态数据视图，这将导致新的应用程序类别，特别是那些涉及分析、跟踪、监测、存档和了解实体随时间演变的应用程序。该项目还将提供机会，在时态数据库、数据分析和大数据的几个关键研究领域对学生进行培训。本次调查得出的结果将被纳入纽约州立大学布法罗分校和加州大学圣克鲁斯分校开设的大规模数据集成高级研究生课程。制作的软件产品和数据集将免费提供给广泛的传播和共享。该项目将通过解决三个基本挑战，推动时态数据的数据管理和集成方面的最新进展。首先，与非时态数据的不完全性不同，时态数据的不完全性可能是随时间变化的。时变的不完全性将需要引入依赖于时间的空值。第二个挑战是时态数据中也可能出现不一致。不一致将通过声明性地指定时间首选项和基于这些首选项来解决冲突的算法来处理。或者，在假设不一致的时态数据库保持不变的情况下，该项目将考虑如何在这样的数据库上计算一致的查询答案。该项目还将首次在一个单一的正式框架内审议既不完整又不一致的数据，这将需要在概念和实践方面取得重大进展。第三个挑战是通过一个概念框架实现时态数据独立性，该框架将使用正式的两层方法来管理时态数据；抽象视图为时态数据的物理表示提供语义和具体视图。这些视图隐藏了较低级别的详细信息，并允许对查询、映射和依赖关系进行声明性的逻辑规范。欲了解更多信息，请访问项目网站http://greenwich.sites.ucsc.edu或http://www.cse.buffalo.edu/~chomicki/.。