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OPeNDAP software
NQuery
A
Network-enabled data-based data selection tool
What is NQuery?
NQuery is a Java-based, network-enabled data-based query tool
that assists the scientist who has selected in-situ datasets
within a desired time-space bounding box, and wishes to refine
that data selection based on characteristics of the data itself.
Examples of such a query might be a request for average temperatures
exceeding a specific value, or values along a bathymetry contour.
Such a capability is particularly important when the data collections
or datasets are very large and located on remote, network accessible
data servers (such as OPeNDAP
data servers).
What problem does NQuery address?
The ability of a scientist to work productively with very large
datasets has been limited because of the difficulties related
to the network transfer of significant subsets of the data, and
the subsequent search through the data for specific observations
or data characteristics of interest. Many different sources of
data are available on the network through OPeNDAP
(in-situ data collections and gridded datasets), yet in order
for scientists to determine whether each data file will suit their
needs, they must sort through each file, wasting time and energy.
This difficulty is compounded when the scientist needs to inter-relate
these results with the extensive climatological data sets that
have been created and are now available directly from the network.
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What is the solution?
We have developed NQuery, a network-enabled data-based query
tool that allows a scientist who has selected datasets that
meet the desired time-space criteria, to then determine whether
each data file will suit their needs, based on the characteristics
of the data within each of the data files. The scientist specifies
the specific desired data characteristics, and the Nquery tool
returns the specific datasets that meet those criteria.
The mechanism used within the NQuery tool is to load pertinent
subsets of user-selected multi-disciplinary datasets into a
temporary, on-the-fly relational database, perform local calculations,
and then uses the scientists specifications to construct sophisticated
SQL queries to locate subsets of interest. A critical design
consideration, with implications for the implementation methodology,
was the speed of this application. Selecting calculations only
as necessary makes the query process as efficient as possible.
Results
NQuery enables scientists to quickly and easily navigate through
pre-selected datasets, filter the data to their needs, and then
use the discovered data in their research.
A simple two-step process takes the user from pre-selected
data to a set of selected data files. The user is unaware of
the complexity of the underlying process. First, the user determines
what observed and computed variables will be included in the
database, and therefore available for subsequent queries. This
selection is accomplished via a graphical interface that lists
all available variables, and computed variables, such as mixed
layer depth, apparent oxygen utilization, and sigma levels.
The space and time ranges can be set to restrict the domain
of interest. A single click then begins working through the
pre-selected dataset to extract and compute the requested variables.
An on-the-fly MySQL database is created and populated as each
data file is processed team.
Where is NQuery used?
Currently, the only desktop application that can ingest the
XML pointer files from NQuery is Java OceanAtlas 4.0 (http://odf.ucsd.edu/joa).
More Information
Contacts
For more information or to acquire NQuery, please contact John
(Oz) Osborne or Donald Denbo
and see the EPIC software
license agreement.
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