The "CJIS Interface" provides a single, unified view of the existing CJIS to the expert systems. Any expert system needs only to specify what data is required, while the details of how to perform the search are the responsibility of the CJIS Interface. Due to the possibly redundant, conflicting, or absent information in a given set of CJIS, the CJIS Interface controls the search of appropriate systems, reconciles conflicting information, and notifies the expert system when data for its request does not exist in the supported CJIS . Expert systems can be constructed for additional applications and have immediate access to all of the information in the existing CJIS. New or modified systems can be added as well, making the new information immediately available to the existing expert systems by updating the CJIS Interface.
The CJIS Interface provides a lower-cost alternative to complete integration of existing CJIS. The CJIS do not have to "talk to" each other in this architecture, nor do they need to know the other systems exist. The CJIS Interface has knowledge about the type of information that resides in the different systems, as well as knowledge about how to access it, effectively integrating the systems from the point of view of the user interface. The systems may be on different machines, with different operating systems, communication protocols, media, and file formats. That information is contained in the CJIS Interface, isolating both the user and the builder of the expert system from the procedural details of providing access to the data in the existing CJIS. In addition, this architecture exploits the inherent parallelism of the CJIS - different searches can be performed on two different CJIS at exactly the same time.
A standardized CJIS Interface, common to all law enforcement agencies, facilitates the proliferation of expert system technology regardless of the CJIS actually in use at a particular site. Because all data access is performed through the CJIS Interface, the expert system can be transplanted to another site with little difficulty. And the interface allows different systems and data to be applied to the problem-solving task, using the same expert system user interface. A common interface provides extensibility to the architecture, as systems can be added on either side of the interface and the increased information made quickly available to the end-user. This standardization applies at local, regional, national, and international levels, enabling geographical expansion of inquiries across dissimilar systems. This would enable, for instance, international policing organizations to identify similar terrorist incidents to aid in the tracking of world-wide terrorist organizations.
Linking multiple, heterogeneous systems through a single interface is a complex task, although implementations [8, 12, 20] and standards  exist. Other interfaces have already been constructed that facilitate rapid prototyping and evolutionary support of complex applications , allowing features to be added or changed easily with no adverse impact on existing functionality. The CJIS Interface incorporates a layered approach to isolate different machine dependencies while taking advantage of a common query and data representation format.
Additional complexity in interface construction is introduced when considering the efficient retrieval of textual information from the large data stores that comprise some CJIS. Even though the search would be limited to those pieces of text that met the limiting qualifications discussed earlier, the efficient processing of the retrieved text must still be addressed. Much of the information necessary to compare MOs, for instance, is stored in the form of text. This information is not indexed in the currently available CJIS to facilitate efficient processing. The time necessary to manually index the existing information comprehensively makes this approach unattractive, while automated full-text indexing techniques suffer problems when advanced compensating techniques are not used . `Smart' indexing of the textual information can be performed by automated indexing tools outfitted with domain-specific indexing knowledge . These indexing techniques, however, require additional work to be completed on the target CJIS. Fortunately, the CJIS Interface takes the available indices in the existing CJIS into account when planning a retrieval strategy , thereby performing a high-level optimization of the retrieval request  that partially eliminates text processing inefficiencies.
Ideally, the law enforcement community can mandate the design of and adherence to a CJIS Interface standard, as has been done for fingerprint identification data interchange , and can include index standardization. This benefits CJIS vendors, expert system vendors, and the law enforcement community itself. CJIS vendors can then focus on developing their base technologies, rather than user interfaces. Expert system vendors are guaranteed a uniform interface for data access which allows them to concentrate on their core technology. End-users realize benefits in increased system compatibility and functionality. One way to enforce a proposed interface standard is to require adherence to the standard in future vendor contracts.
In the absence of a formal standard and vendor participation, an interface can still be constructed for a particular site. An interface designed with only a small subset of systems in mind, however, is sure to suffer portability and extensibility problems. Still, for a single site, this is a lower-cost method for integrating existing systems and providing in-house extensibility of systems than a full-scale system-level integration effort.
Police departments are labor-intensive organizations. The single highest recurring cost is salaries. The advent of expert systems in the criminal justice system community will provide for the more efficient use of human resources to focus on crime prevention. Expert systems, coupled with integrated data stores, significantly reduce personnel costs by saving time in collecting, evaluating, and searching for information . Quicker suspect identifications saves investigative staff-hours and reduces serial offenses.
The expert system "front-ends" operate in a stand-alone fashion for training purposes, continuously available for consultation. In this capacity, the expert systems perform as "on-line mentors" for the novice at a fraction of the cost of providing a human expert. The steep learning curve associated with becoming technically proficient in a given specialty is overcome more quickly and cost-effectively, because the systems not only advise `what' to do but `why.'
Enormous sums are invested in current CJIS, while equally large amounts are annually invested in law enforcement personnel salaries. As expert system technology becomes available in the commercial marketplace, it enables the law enforcement community to significantly leverage its computer and human resources. Considerable additional benefits are gained by standardizing an interface to use this new technology. Doing so will preserve the commitment in existing resources, greatly enhance the abilities of law enforcement personnel through integration and intelligent use of systems, and provide a mechanism for system portability and growth at the local, regional, national, and international levels.
 ANSI/NBS - ICST 1-1986, American National Standard for Information Systems - Fingerprint Identification - Data Format for Information Interchange, American National Standards Institute, New York, NY.
 Bachman, C., Ross, R., "Toward a More Complete Reference Model of Computer-Based Information Systems," Computer Networks, Vol. 6, 1982.
 Bayse, W. A., Morris, C. G., "FBI Automation Strategy: Developing AI Applications for National Investigative Programs," in Signal, Vol. 41, No. 9, May 1987.
 Date, C. J., An Introduction to Database Systems, Vol. 1, 4th Edition, Addison-Wesley Publishing Co., Reading, Mass., 1986, p. 339.
 Harmon, Paul, King, David, Expert Systems - Artificial Intelligence in Business, John Wiley & Sons, Inc., NY, 1985.
 Humphrey, Suzanne, "Illustrated Description of an Interactive Knowledge Based Indexing System," in Proceedings of the Tenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New Orleans, June, 1987. Yu, C. T., Van Rijsbergen, C. J., Eds., ACM Press, New York, New York.
 Jakobson, G., Lafond, C., Nyberg, E., Piatetsky-Shapiro, G., "An Intelligent Database Assistant," in IEEE Expert, Vol. 1, No. 2, 1986.
 Jakobson, G., Piatetsky-Shapiro, G., Lafond, C., Rajinikanth, M., Hernandez, J., "A Knowledge-Based System for Integrating Multiple Heterogeneous Databases," in Proceedings of the Third International Conference on Data and Knowledge Bases; Improving Usability and Responsiveness, Jerusalem, Israel, June 1988.
 Jones, A. D., Western Identification Network Request for Purchase (RFP), 1988.
 Kellogg, Charles, O'Hare, Anthony, Travis, Larry, "Optimizing the Rule-Data Interface in a KMS (Knowledge Management System)," in Proceedings of the Twelfth International Conference on Very Large Databases, August, 1986.
 King, J. J., Query Optimization by Semantic Reasoning UMI Research Press, Ann Arbor, Michigan, 1984.
 Landers, T., Rosenberg, R., "An Overview of Multibase," in Proceedings of the Second International Symposium on Distributed Databases, September, 1982.
 Laudon, Kenneth C., "Data Quality and Due Process in Large Interorganizational Record Systems," in Communications of the ACM, Vol. 29, No. 1, January, 1986.
 Laudon, Kenneth C., Dossier Society: Value Choices in the Design of National Information Systems, Columbia University Press, 1986.
 "Artificial Intelligence is Brainchild for Feds," in Law Enforcement Technology, September/October 1988.
 Lucas, R., "An Expert System to Detect Burglars Using a Logic Language and a Relational Database," in Proceedings of the Fifth British National Conference on Databases, Kent, England, July 1986.
 Lynch, K. J., Hoopes, L. M., "A Generic Query Processor for Retrieval," in Proceedings of the Fall Ingres Users Association Conference, Tampa Bay, Florida, Nov. 1987.
 Lynch, K. J., Hoopes, L. M., "An Interface for Rapid Prototyping and Evolutionary Support of Database-Intensive Applications," to appear in Proceedings of the IEEE International Phoenix Conference on Computers and Communications, March, 1989.
 Martorelli, William P., "PC-Based Expert Systems Arrive," in Datamation, Vol. 34, No. 7, April, 1988.
 Martin, James A., Oxman, Steven, Building Expert Systems, Prentice-Hall, Englewood Cliffs, NJ, 1988.
 McHenry, W. K., Lynch, K. J., Goodman, S. E., "Handling Textual Information in a GDSS Database: Experience with the Arizona Analyst Information System," in Proceedings of the Twenty-first Annual Hawaii International Conference on System Sciences, Jan. 1988.
 Moses, Kenneth R., "A Consumer's Guide to Fingerprint Computers," in Identification News, June 1986.
 Phoenix Police Department CAPRI Users Manual, 1976.
 Phoenix Police Department PACE System Overview, September, 1988.
 Ratledge, Edward, University of Delaware, Newark, NJ, Personal Communication, October 19, 1988.
 Ryan, Alan J., "Expert System Stalks Killers," in Computer world, Vol. 21, No. 28, July 1987.
 Sadasivam, V., Subramanian, R. K., "An Intelligent Computer System for Forensic Science," in Proceedings of TENCON 87: 1987 IEEE Region 10 Conference 'Computers and Communications Technology Toward 2000,' Seoul, South Korea, August, 1987.
 "Text Processors Will Help in Murder Enquiries," in Data Processing, Vol. 27, No. 4, May 1985.
 Vedder, R. G., Mason, R. O., "An Expert System Application for Decision Support in Law Enforcement," in Decision Sciences, Vol. 18, No. 3, Summer, 1987.
 Wilkins, Bryan, "FBI Moving to Employ AI Software as Crime Fighter," in Computerworld, Vol. 19, No. 5, February, 1985.