BBN Technologies

Semantic technologies are revolutionizing the way in which we address large datasets and cross-domain integration, but they pose new challenges such as the issue of ontological alignment. People observe the world from differing perspectives and semantic technologies allow us to capture these perspectives in a clean, structured manner that encourages universal sharing. To an auto manufacturer, a truck is a product. To a traffic analyst, a truck is simply a vehicle to be counted. To a shipping company, a truck is a means of conveyance. In order for these assumptions about the world to be shared and reused, alignment is required.

Aligning conceptual models is a difficult challenge. Each model may use different terminology and different levels of detail to formalize ideas and the relationships that define them. Current solutions often require countless hours of manual intervention, are complicated to implement, and can be very costly. BBN solves this problem with the release of a powerful ontology mapping tool called Asio Cartographer. A key feature is the intuitive interface that makes data model mapping quick and easy while preventing errors associated with manually editing complex rules. Asio Cartographer exploits our innate ability to think visually to simplify the alignment process.

Asio Cartographer is a graphical, ontology mapper that is based on the Semantic Web Rule Language (SWRL). It utilizes the core functionality of the Snoggle open source mapping tool to assist in aligning ontologies represented in the Web Ontology Language (OWL). It allows users to visualize ontologies and then draw mappings between them on an intuitive graphical canvas. Users draw mappings as necessary and Cartographer transforms them into SWRL/RDF or SWRL/XML for use in a knowledge base.

Cartographer replaces the laborious task of manually writing rules in a text editor by providing a canvas on which to conceive mappings visually. The canvas is divided into two regions: from and to. The "from" region contains a structure in the source ontology, and the "to" region contains the corresponding structure in the destination ontology. This arrangement models a user’s common view of mapping structures. Arrows are drawn between the two regions in order to show mappings. For example, a Person who is 6 feet, 2 inches tall in one ontology may be represented as an Employee who is 74 inches tall in another ontology.

Cartographer also supports the default SWRL built-ins and allows for easy insertion of your own custom SWRL built-in definitions. Built-ins can be thought of as functions that perform calculations or actions as part of a rule. An example built-in might add two numbers or transform a data type. Consider a mapping between two ontologies where one uses a numeric representation for date (e.g. 20070315) and the other users a string (e.g. March 15, 2007). A custom built-in could be used to convert between the two representations. Cartographer’s ability to provide built-in customization opens up entirely new possibilities for handling and easing alignment, all without the need for another tool or without sacrificing the use of semantic web standards.

Complex rules are easily created by dropping types defined in the ontologies onto the canvas and linking them with relationships. Cartographer provides the ability to export these mapping rules for use in a knowledge base capable of SWRL inference.