Digital Government: Very Large Scale Multidimensional Data Management and Retrieval for USGS and NIMA Imagery

EIA-9983430 Zhang，AidongSUNY BuffaloDigital Government：Very Large Scale Multidimensional Data Management and Retrieval for USGS and NIMA Imagery该项目将对管理和检索合作伙伴政府机构（美国地质调查局（USGS）和国家成像和制图局（NIMA））持有的多维数据进行研究。 在这样的应用中，分布在远程位置的地理图像数据库必须在其他位置可用，以便进行数据检索。 随着基于内容的图像数据检索的出现，传统的数据库设计和查询搜索方法将不适合在开发分布式图像检索系统，所提出的研究的目的是调查新的方法，以支持有效和高效地访问集成的地理图像数据库在互联网上。 这些方法将为分布式地理图像检索系统的设计奠定基础。 与这种集成的设计有关的技术挑战是在图像数据库之上创建元级系统。 具体的研究目标是：（1）识别多尺度表示（2）研究可以检测多维图像数据的任意形状的聚类的新颖聚类方法，（3）构建元数据模型，该元数据模型制定集成系统将可视查询引导到相关数据库所需的元数据，（4）发展基于元数据的数据库选择方法的理论基础;（5）设计新的可视化查询处理方法，整合从可视化数据内容中提取的异构特征。在项目期间，USGS和NIMA将提供所有必要的影像数据集及其类别。 在项目期结束时，将在美国地质勘探局和国家海洋和大气管理局两个地点推广一个系统。 通过上述研究活动，将提供基本的理解和新的技术，以支持在互联网上分布的多维数据的分布式卷的设计，并将发现广泛的应用，作为模板，在其他政府机构，如美国宇航局的分布式图像数据库系统的开发。 所产生的实验结果可以用来建立有效的基准评估分布式图像数据检索系统的性能。

EIA-9983430Zhang, AidongSUNY BuffaloDigital Government: Very Large Scale Multidimensional Data Management and Retrieval for USGS and NIMA ImageryThis project will conduct research on managing and retrieving multidimensional data held by partner government agencies (the United States Geological Survey (USGS) and the National Imaging and Mapping Agency (NIMA)). In such applications, geographic image databases distributed at remote locations must be made available at other locations for purpose of data retrieval. With the advent of content-based retrieval of image data, traditional methods for database design and query search will not be suitable in developing distributed image retrieval systems.The objective of the proposed research is to investigate novel approaches to supporting effective and efficient access to the integrated geographic image databases over the Internet. These approaches will establish a foundation for the design of distributed geographic image retrieval systems. The technical challenge relating to the design of such integration is the creation of meta-level system on top of the image databases. The specific research goals are : (1) identify multi-scale representation (multidimensional) methods for geographic images, (2) investigate novel clustering approaches that can detect clusters of arbitrary shape of multidimensional image data, (3) construct a metadata model that formulates the metadata that are needed for the integrated system to direct a visual query to relevant databases, (4) develop the theoretical foundation of database selection approaches based on the metadata, and (5) design novel visual query processing approaches that integrate heterogeneous features extracted from the content of visual data.During the project period, USGS and NIMA will provide all necessary imagery data sets and their categories. A system will be disseminated at both USGS and NIMA sites at the end of the project period. Through the above research activities, the fundamental understanding and novel techniques will be provided to support the design of distributed volume of multidimensional data distributed over the Internet and will find broad applications as a template for the development of distributed image database system in other government agencies, such as NASA. The experimental results to be generated can be used to establish effective benchmarks for assessing the performance of distributed image data retrieval systems.