3. Grid Concepts – “Dimension”
Some examples:
1-D Grid: e.g., a set of temperature measurements taken at
various depths in a vertical line in the ocean
2-D Grid: e.g., a set of these 1-D grids at different points
along an east-west line.
3-D Grid: e.g., a set of these 2-D grids at different points
along a north-south line
4-D Grid: e.g., a set of these 3-D grids, each pertaining to a
different day and time
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4. Gridded Data Application Areas
Modeling applications
Meteorology
Oceanography
Climate Modeling
Fluid Dynamics
Data analysis applications
Nondestructive testing
Geophysics
Medical Imaging
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7. Grids and the Grid DataBlade
For storage and manipulation of grids, where
data volumes are too large to be kept in memory, or
data extractions are small relative to the amount of
data stored, or
the data needs some form of resampling
BCS's Grid DataBlade can
efficiently handle very large multidimensional
gridded datasets
speed up extraction of data products 50-fold or more
rapidly generate subsampled data along parallel or
oblique axes
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8. For more information …
Website: http://www.barrodale.com
Contact: BCSInfo@barrodale.com or (250) 412-7428
More: http://www.barrodale.com/GridBladeinDepth.pdf
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Editor's Notes
Here’s a piece of a gridded dataset created by recording ocean measurements every hour at spacings every one meter in depth and every ten meters in two horizontal dimensions (northing and easting). This dataset is a 4D grid having three spatialdimensions (northing, easting, and depth) and one temporaldimension, which is not shown here.Three variables (temperature, salinity, and pressure) are attached to each grid point, as illustrated in the diagram.
Gridded data comes in a variety of shapes and sizes. By shape, we mean the number of dimensions the grid has and by size, we mean the number of points in each dimension.
Broadly speaking, gridded data arise in two main areas of application: modeling applications –often involving the numerical solution of differential equations – and data analysis applications.
This slide demonstrates extraction of an oblique slice of a 3D gridded dataset. The ability to extract oblique slices efficiently is an important feature of the BCS Grid DataBlade; it has application not only in medical imaging, but also in non-destructive testing, exploration for diamonds, meteorology, hydrology, oceanography, etc.
The Navy generates weather and ocean forecasts on a global basis, leading to very large gridded databases of environmental attributes that are updated several times per day. Often, all that the user requires is a “slice” or perhaps a “stick” of such information. The Grid DataBlade processes queries on the database server, thereby minimizing the amount of network input/output and client-side CPU time required.
The Grid DataBlade is ideally suited for applications involving any of the requirements listed in the top three bullets; in short, the Grid DataBlade makes it easy to work effectively and efficiently with gridded data in a database.
This concludes our mini presentation on the Grid DataBlade─ a database extension for handling multidimensional gridded datasets. Thank you for your interest. For more information please visit our website, send us an email, or give us a call.The final bullet above points to an in-depth down-loadable presentation on the Grid DataBlade. Goodbye for now.
