Integrating and querying information sources in the context of large-scale ontological knowledge

信息丰富，并且引入具有大容量存储器的商业上可行的计算机系统来帮助管理信息，这促进了数据库系统以及基础技术的发展。到目前为止，最成功的是基于关系数据模型的系统。这样的系统提供了一个干净的概念领域特定的接口管理信息。这使应用程序开发人员不必了解现有数据源的低级接口及其物理数据组织，也不必选择适当的数据结构和算法。因此，对于关系数据库系统，发现有效的执行策略，称为计划，用于数据操作请求，称为查询和更新，已经成为研究的焦点超过三十年。 数据库系统技术的当前实践已被证明对于对应于数据库系统的商业类应用的信息系统非常有效。在这种情况下，概念接口是直接的，数据源相对简单，例如，对应于驻留在大容量存储介质上的记录文件，其中记录值没有内在的底层结构。然而，当概念接口依赖于捕获应用领域的更复杂和更广泛的本体知识的能力时（例如，在健康信息学中或在语义网上的信息检索中），或者当数据源中的记录值可能被排序或对应于实现链接数据结构的指针时（例如，在主存储器数据源的数据集成中）。拟议的研究计划的目标是扩大数据库技术的范围，克服许多这些限制的方式。特别是，该计划将继续就一些研究课题开展持续的合作工作，这些研究课题可以导致新的和更全面的方法，以解决将用户查询和更新转换为低级别数据源的有效计划的基本问题。

Information abounds, and the introduction of commercially viable computer systems with mass storage to help manage information has prompted the development of database systems together with an underlying technology. By far the most successful are systems that are based on the relational data model. Such systems provide a clean conceptual domain specific interface to managed information. This shields application developers from the need to understand low level interfaces to existing data sources and their physical data organization and from the need to choose appropriate data structures and algorithms. Hence, for relational database systems, discovering efficient execution strategies, called plans, for data manipulation requests, called queries and updates, has been the focus of research for more than thirty years. The current practice for database system technology has proven to be very effective for information systems that correspond to business-like applications of database systems. In such cases, the conceptual interface is straightforward and the data sources are comparatively simple, for example, corresponding to files of records residing on mass-storage media in which record values have no intrinsic underlying structure. However, the application to other areas of data management has proven to be much more difficult when the conceptual interface relies on an ability to capture more sophisticated and extensive ontological knowledge of an application domain (e.g., in health informatics or in information retrieval over the semantic web), or when record values in data sources might be ordered or correspond to pointers that implement linked data structures (e.g., in data integration for main memory data sources). The objective of the proposed research plan is to broaden the scope of database technology in ways that overcome many of these limitations. In particular, the plan is to continue ongoing collaborative work on a number of research topics that can lead to new and more comprehensive approaches to the fundamental problems of translating user queries and updates to efficient plans over low level data sources.