Information Integration of Heterogeneous Data Sources

描述（由申请人提供）：本提案的总体目标是开发信息集成架构和相关工具，以支持来自分布式异构数据源的数据和知识的快速集成。该体系结构旨在为生物医学研究提取连贯的知识库，提高提取知识的准确性，完整性和质量发挥重要作用。为了实现这些目标，建议的可扩展架构包括新的创新的广义集成算法和工具，用于生成的调解人，以捕获数据源的功能行为，语义表示的数据源，以支持自动生成的集成代理，并优化集成的数据查询。信息集成体系结构与不断发展的基于Internet的XML电子数据交换、语义Web服务和Web服务发现标准保持同步。因此，利用互联网技术和标准的目的，提供持久的国家的最先进的解决方案的信息集成。此外，所提出的架构是固有的可扩展性方面的数据源，可以集成，用户的集成系统的数量，以及可以解决的生物医学问题的范围。在该项目的第一阶段，将开发拟议的整合算法和工具的原型，作为概念证明，并在可扩展性和整合能力方面，利用私人和公共数据源，为评价和试点测试拟议的整合机制奠定基础。

DESCRIPTION (provided by applicant): The overall goal of this proposal is to develop an information integration architecture and associated tools to support rapid integration of data and knowledge from distributed heterogeneous data sources. The architecture aims to play a significant role in extracting coherent knowledge bases for biomedical research and improving the accuracy, completeness and quality of the extracted knowledge. Towards achieving these goals, the proposed scalable architecture includes new innovative generalized integration algorithms and tools for the generation of mediators to capture the functional behavior of data sources, semantic representation of data sources to support automated generation of integration agents, and optimization of integrated data queries. The information integration architecture keeps pace with the evolving Internet-based XML electronic data interchange, semantic web services, and web services discovery standards. Thus, leveraging the Internet technologies and standards for the purpose of providing lasting state-of-the-art solutions for information integration. In addition, the proposed architecture is inherently scalable in terms of the number of data sources that can be integrated, the number of users of the integrated system, and the range of biomedical problems that can be tackled. During phase I of the project, prototypes of the proposed integration algorithms and tools will be developed as proofs of concept and to form the foundation for evaluation and pilot testing of the proposed integration mechanisms, using private and public data sources, in terms of scalability and integration capabilities.