IMT^®

The Intelligent Mapping Toolkit (IMT®) was developed for the United States Transportation Command (USTRANSCOM) in 2005 to promote interoperability between automated information systems. To this end, IMT® supports USTRANSCOM-affiliated data analysts by discovering semantic relationships between elements of two or more data sets. By doing so, IMT® enables those analysts to quickly map similar but differently named data across multiple data sets.

History of IMT®

As USTRANSCOM’s deployment and distribution responsibilities expand, more efficient data interoperability is required. To accomplish this greater interoperability, USTRANSCOM sponsored several pilot programs that collectively yielded two key enablers of interoperability. The first was an enterprise-wide data model, known as the Distributed Process Information Exchange Data Model (DPIEDM), which enables interoperability at the metadata (i.e., database schema) level. The second was a formalized program for the identification, management, and distribution of enterprise reference data, known as the TRANSCOM Reference Data Management (TRDM) program, which enables interoperability at the instance data (i.e., database record) level.

Although essential to efficient interoperability, using the DPIEDM and TRDM required human data analysts to develop and maintain semantic mappings between automated information systems—a time-consuming and error prone requirement to accomplish. To enable greater mapping accuracy in less time, USTRANSCOM contracted CDM, in collaboration with Knexus Research Corporation, to research and develop technology that would assist analysts in using the capabilities of the DPIEDM and TRDM and, thereby, in standardizing methods of data transfer between various information systems. Out of this research came IMT®, a multi-agent software framework that utilizes metadata and instance data mappings to intelligently and quickly generate mappings between systems.

IMT® Functionality

• Uses intelligent agents to automate significant aspects of meta-maps and instance maps. Meta-maps link similar columns of data in different data sets, such as columns entitled "First Name" and "Name One." Instance maps generate links between corresponding rows of data using a unique primary key, such as a National Stock Number.




• References domain-specific lexicons and thesauri to discover similarities, abbreviations, and synonyms in different sets of data.




• Presents possible mappings with detailed explanations to users for approval.

IMT® can help standardize data between systems, maintain consistency between data sets, and determine the accuracy of data. Contact Us to learn more about our IMT® technology.