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

在当今的数字世界中，关于实体的不完整和不一致的信息通常可以在多个不同的数据源中找到，或者在不同时间在同一源的不同版本中找到。 为了利用丰富的可用信息量，许多组织随着时间的推移对公共（和私有）数据进行管理和集成，以创建相关实体的全面时态视图。 该项目将有可能通过开发数据管理和集成的软件原型来产生重大的社会影响。 这种原型将使用户能够根据需要对时态数据建立健全、针对具体应用的一致看法，从而产生新的应用类别，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类别。 该项目还将为学生提供培训时间数据库，数据分析和大数据的几个关键研究领域的机会。 在这项调查中获得的结果将被纳入高级研究生课程提供的大规模数据集成在纽约州立大学布法罗和加州大学圣克鲁斯。 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整合的最新技术。 首先，与非时态数据中的不完整性不同，时态数据中的不完整性可能是时变的。时变不完全性将需要引入时变零点。 第二个挑战是时态数据中也可能出现不一致。不一致性将通过声明性地指定时间首选项和算法来处理，以根据这些首选项解决冲突。或者，在不一致的时态数据库保持不变的假设下，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际方面取得重大进展。 第三个挑战是通过一个概念框架来实现时态数据的独立性，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。 视图隐藏了较低级别的细节，并允许查询、映射和依赖关系的声明性、逻辑规范。欲了解更多信息，请访问项目网站www.example.com或www.example.com。

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/.