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 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 data-requirements expansion 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.

Data-quality metrics process 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.

JSC database data quality 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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04/04/12

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