Joint Spectrum Center databases
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Joint Spectrum
Center's data-quality metrics program
By Stuart Kennison and Jamileh Soudah
The Defense Department tasked the Joint Spectrum Center
in Annapolis, Md., to develop and maintain an extensive set of databases that
directly support both the spectrum-management and
electromagnetic-environmental-effect communities. We?re dedicated to
maintaining our databases at the highest quality level possible. To accomplish
this task, we established the data-quality metrics program to monitor and
enhance the quality of our databases.
JSC, part of the Defense Information Services Agency, has
the unique role of supporting achievement of information/decision superiority
and full-spectrum dominance by providing services and products to the defense
secretary?s office, the Joint Staff, unified commands, military departments
and defense agencies to ensure DoD effectively uses the EM spectrum. We strive
to provide support and guidance that will result in fielding warfighters
equipment and systems that operate compatibly in their EM environments.
JSC database program
To support warfighters, we maintain several databases
containing technical and administrative data.
Follow the
link
for a description of the five primary databases JSC maintains. Each
database provides information for a range of applications the warfighter needs
(following figure).
|
Examples
of JSC data uses.
|
Future challenges
The demand for spectrum management and E3 data is rapidly
increasing. As more of the EM spectrum is used by both commercial and military
systems, there?s an increased potential for interference. With this increase
in spectrum crowding, it?s becoming more difficult to ensure maximum
performance of warfighter systems. As a result, there?s an increasing demand
for JSC data, which is used to analyze and predict operational performance of
warfighter systems.
In addition, Joint Vision 2010 and Joint Vision 2020 have
significantly increased requirements to support warfighter spectrum management
and interference resolution. Also, the quantity and complexity of newer, more
advanced telecommunications and radar systems have progressively increased.
Today the warfighter must ensure EM compatibility in diverse areas of the world
for both joint and coalition force deployments. These new warfighting
requirements are significantly increasing the need for better-quality JSC data
(figure below).
|
Joint
Vision 2020 is expanding JSC data requirements.
|
To meet future challenges, JSC must maintain more
accurate, complete and current data. To accomplish this, we?re implementing
specific quality improvements in our data resources. These data-quality
improvements will focus on meeting two main JV2010/20 goals:
information/decision superiority and full-spectrum dominance.
Data-quality metrics program process
JSC established its data-quality metrics program to meet
JV2010/20?s challenges. Our goal is to monitor and improve the overall quality
of our databases by using a standard set of data-quality metrics. Based on
industry?s best practices in data-quality management, we measure three primary
attributes of data quality: accuracy, completeness and currency.
As the following figure illustrates, JSC?s data-quality
improvement process is continuous and starts with defining data-quality metrics
and establishing database-specific quality goals. This is followed by measuring
the quality of the data in each database, assessing the data quality relative to
the quality goals, and defining and implementing database quality-improvement
initiatives.
|
JSC
data-quality metrics process.
|
Once we complete this assessment and data-improvement
process, we reassess the data-quality goals and the process continues.
Data-quality measures
Standard units of measure are used to quantify the three
quality attributes we?ve mentioned (accuracy, completeness and currency) for
each of our primary databases. Definitions of the data-quality attributes, with
specific units of measure we use to measure data quality, are described in the
linked table
.
In Fiscal Year 2000, we implemented automated measurement
capabilities to measure about 70 percent of these data-quality units of measure.
More automated capabilities were developed and put in place for FY01 so we could
measure the quality of nearly all our data.
Database-improvement initiatives
We?ve initially assessed the quality of data in our
databases. Since the capability to objectively measure data quality doesn?t
exist now for some databases, JSC is developing automated capabilities so
objective measurements can be made in the near future.
The figure below shows the results of our
data-quality assessment. This table identifies the measured JSC data quality for
the five primary JSC databases. There are several areas where we need to improve
the quality of our data to fully support user requirements. To mitigate these
deficiencies, we?ve identified specific database-improvement initiatives we?ll
describe next.
|
Measured
data quality of JSC databases.
|
Task 1:
add electronic-warfare integrated
reprogramming/electronic-order-of-battle data in equipment characteristics/space
and background-environment-information databases. Our user community has
requested more source data on foreign equipment. The Defense Intelligence Agency
maintains the electronic-order-of-battle database, which contains location
information on foreign fixed and mobile equipment. Under this task, the
collateral (secret) version of EOB will be integrated into our BEI database.
Since EOB records only identify equipment location, the
equipment?s technical characteristics will have to be captured from a separate
source. We?ll capture this equipment data by integrating the EWIR database,
which was developed by the National Air Intelligence Center, into our EC/S
database. We?ll then establish a link between the BEI and EC/S databases to
augment EOB location records with equipment-characteristics data.
Meeting this task will help us with our goals of the
"completeness" quality attribute. Quality improvement is estimated at
10-percent improvement in completeness of foreign frequency-assignment data. The
benefit is that we?ll add needed data on foreign systems. The warfighter will
then be able to carry out spectrum management and interference resolution in
foreign countries more effectively.
Task 2:
capture and maintain more system data in the EC/S
database. JSC maintains data on DoD communications and radar systems. We
maintain very limited technical data on commercial systems the warfighter
interacts with, on electronic-warfare systems or on military digital networks.
Since these systems? performance directly impacts the warfighter?s mission
effectiveness, we must be able to capture and maintain technical data needed to
perform E3 analyses on these systems.
Meeting this task will also aid us in our completeness
quality goals. We estimate quality improvement at 6 percent of EC/S database
completeness. This will enable JSC to analyze the effect of interference to/from
commercial, EW and digital-networks systems. Consequently, we?ll be able to
assess warfighter overall mission effectiveness in the complete battlespace.
Task 3:
develop a software capability to augment
Frequency Resources Record System and BEI data. We maintain frequency-assignment
data in the FRRS and BEI databases that?s provided by outside sources. Many
records have missing technical data. This task will be to develop a software
capability to identify missing and incorrect technical data in these databases
and, where possible, to add estimated (technically correct) data values. When we
find incorrect data, both the source-provided values and expected technically
correct values will be stored in the database.
Meeting this task will drive us toward the quality
attribute of completeness. Quality improvement is estimated at 15 percent in the
accuracy of frequency-assignment data. Completeness of JSC frequency-assignment
data will improve and, in turn, this will enable DoD to identify, resolve and
avoid interference problems associated with warfighter systems.
Task 4:
review Spectrum Certification System data. The
SCS database contains data from applications for frequency allocation (J/F-12)
each military service provides. This task will provide a periodic technical
review of existing J/F-12 data in the SCS database. We?ll do an engineering
review of 600 J/F-12s each year. Where we find inaccurate data, we?ll contact
the responsible services to update their J/F-12 records. We?ll also use the
results of each year?s data reviews to estimate the accuracy of the entire SCS
database.
Meeting this task will ensure accuracy in our databases
and give us up to a 10-percent improvement in the accuracy of our
frequency-allocation data. We believe the accuracy of DoD?s
spectrum-certification data will improve. Both spectrum management and
interference resolution of warfighter systems will consequently improve.
Conclusion
We?ve developed a comprehensive approach to monitoring
our databases? quality to identify the best areas for database improvements.
The process we?ve implemented, which is based on industry?s best practices,
has proven to be effective in quantifying and evaluating the quality of data
maintained in our databases.
JSC is continuing to develop and refine its data-quality
metrics program. By the end of FY01, we had in place a full suite of automated
capabilities to measure data quality across all our databases. Specific
database-improvement initiatives are already in the works, as we?ve outlined
in this article, to improve areas of lower data quality.
We?re dedicated to providing quality data that meets
the warfighter?s needs. Through our data-quality metrics program, we are
continually monitoring, evaluating and improving our data quality to better meet
the warfighter?s future information needs under JV2010/20.
Mr. Kennison is data administrator and division manager
for database operations at IIT Research Institute, Annapolis. Under his
oversight is JSC?s long-range planning of data resources. He?s responsible
for coordinating user requirements, planning data access and implementing new
quality controls for the various JSC databases. He has supported JSC for 30
years and has extensive experience as both user and supplier of spectrum
management and E3 data. For a large part of his career, he was a project
engineer and manager supporting Army and Air Force projects at JSC. Now he is
applying that data-user experience to develop and enhance the quality of JSC?s
databases.
Ms. Soudah is team leader and project manager for the
database and modeling and simulation programs at JSC. She is a software engineer
with more than eight years? experience. She has worked as software engineer
and program integrator for the Army Digital Topographic Support System and F-15S
simulator at the Defense Contract Management Agency in Akron, Ohio. As senior
software engineer at the DCMA Lockheed Martin Sander in Nashua, N.H., Ms. Soudah
was responsible for overseeing development of many research-and-development
programs such as rapid prototyping of application-specific signal processors.
She worked at the DCMA software center in Boston, Mass., as software program
manager before she joined JSC?s staff. She has a bachelor?s degree in
electrical engineering from Kuwait University and a master?s in electrical
engineering-communications from the University of Wisconsin.
Acronym QuickScan
BEI ? background-environment information
CE ? communications-electronics
DCMA ? Defense Contract Management Agency
DoD ? Department of Defense
E3 ? electromagnetic environmental effect
EC/S ? equipment characteristics/space
EM ? electromagnetic
EOB ? electronic order of battle
EW ? electronic warfare
EWIR ? electronic-warfare integrated reprogramming
FRRS ? Frequency Resources Record System
FY ? fiscal year
JSC ? Joint Spectrum Center
JV ? Joint Vision (2010/2020)
SCS ? Spectrum Certification System
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