By annotating data semantically, the meaning of critical information can be understood by computers as well as humans, making it easier to find and establish connections with other information even if it is stored in different locations within multiple databases and across complex systems.

Sophisticated Financial Operations Metric Analytics and Advanced Interactive Reporting.

The sophisticated semantic technology is seen in the power and interactive functionality given to users. A user can compose custom financial summaries simply by selecting their desired metrics.

For example, by selecting all of the Accounts Receivable metrics, the semantic technology is able to generate a graph representing the combined real-time statuses across all three of these usually separate metrics. 

How is this possible? The financial data is populated into a common financial metric ontology. Conversion to this semantic domain is done in real-time so the system can render the data to meet each user’s specific demands. 

High level drill-down capabilities allow users to view summary comments, actual values, and goal amounts before diving into the component details. Synopsis of problem areas and any corrective actions being taken are also readily available. Historical views for each metric are available directly within the application. Since EBI’s ontology is operating directly off of the trusted data source, the system is always up-to-date for full accountability and transparency.

Semantic Methodology: Refined for Rapid Development. 

A vast amount of financial data exists across military service lines housed in multiple databases. Faced with hundreds of thousands of triples, the CSCI developers took a direct and simplified approach; they recognized a need to use as much existing open source software as possible to minimize bugs and optimize running efficiency. The CSCI development team used Protégé, Jena, and several common JavaScript technologies to maximize user experience and system performance while delivering a robust product.

Taking advantage of existing development engines, the CSCI Consulting team reduced the risk for potential errors and refined the delivery process. By using these methods, the CSCI developers went from design to defined OWL ontology within only three weeks. By using the Jena libraries, the system was easily able to parse and serialize the data into any requested syntax, including Turtle/N3, RDFXML, and JSON formats. Best of all, since the system is semantically aware, all of these outputs are generated from the source ontological data in real-time making development more efficient, easier to maintain, and object oriented.

Designed for Secure Environments.

Since all of the ontologies were created dynamically from existing (secure) database queries, the result set is automatically filtered based on the user’s security rights and other user-defined parameters. This solution removes the costly and complex overhead associated with creating and maintaining security within a secure triple store source. Real-time semantic queries make it possible to instrument existing data sources as ontologies, while still accommodating the complex nature of this unique security environment.