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Exploiting HDF5 Technologies to Represent Geo-Information

Exploiting HDF5 Technologies to Represent Geo-Information. Peter Cao, Jacob Grubar , Mike Folk The HDF Group. An Example with Complex Terrain Data. Acknowledgment. This work was funded by

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Exploiting HDF5 Technologies to Represent Geo-Information

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  1. Exploiting HDF5 Technologies to Represent Geo-Information Peter Cao, Jacob Grubar, Mike Folk The HDF Group An Example with Complex Terrain Data HDF and HDF-EOS Workshop XIV

  2. Acknowledgment This work was funded by US Army Corps of Engineers, Engineering Research and Development Center (ERDC), BAA Contract No. W9132V-08-C-0028 Special thanks to John Nedza of ERDC-TEC, whose ideas are the basis for this work. HDF and HDF-EOS Workshop XIV

  3. Goals of This Study • Explore a unified data model for information retrieval, visualization, and analysis • Identify the role that HDF5 can play as a data management platform for Battlefield operations • Demonstrate the use of web-based tools in combination with HDF5 to organize and work with a wide range of operational data HDF and HDF-EOS Workshop XIV

  4. HDF5 Capabilities HDF and HDF-EOS Workshop XIV

  5. Variety and Scale lat | lon | temp ----|-----|----- 12 | 23 | 3.1 15 | 24 | 4.2 17 | 21 | 3.6 • Store almost any type of data • Physical terrain (grid, vector) • Human terrain (about people) • Multimedia (video, etc.) • Scale efficiently • From low resolution images to high resolution images Experiment Notes: Serial Number: 99378920 Date: 3/13/09 Configuration: Standard 3

  6. Relationships Grouping, metadata, other features show relations among data entities. / SimOut Parameters 10;100;1000 Timestep 36,000 City A lat | lon | temp ----|-----|----- 12 | 23 | 3.1 15 | 24 | 4.2 17 | 21 | 3.6

  7. Demo • Uses Qt user interface frameworkas a web-browser plugin • Demo will focus on: • Heterogeneous Information Layers • Dynamic Data Management • Multidimensional Scales • Scalable Data Structures HDF and HDF-EOS Workshop XIV

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