Overview

The ModelMosaic® toolkit provides automatic knowledge extraction from multi source text data, allowing you to construct and visualize knowledge in the form of ontologies and process models.

The ModelMosaic® toolkit is ontology configuration and capture software that provides automatic knowledge extraction from multi-source text data, allowing users to construct and visualize knowledge—in the form of ontologies and process models—via an easy to use graphical interface. The ModelMosaic® toolkit is based on the Unified Modeling Language (UML) and the IDEF5 ontology description capture method, the government standard for object oriented modeling. The toolkit also provides IDEF3 process modeling, and future development will add the IDEFØ function modeling method.

The ModelMosaic® toolkit lets you extract the essential nature of concepts in the ontology domain and to document the behavior of entity relations according to the inferences that can be made with them. The ModelMosaic® toolkit includes an ontology management component that lets you archive and collect ontologies that can be selectively analyzed, compared, pruned, and combined for use in new system development projects. The toolkit also provides import and export capability to other ontology modeling languages like OWL and UML, and is plug-compatible with other OWL-based ontology editors such as Protégé.

Features

	Structured and unstructured data analysis
	Automatic text ontology extraction
	Ontology and schema mediation and comparison
	Data transformation via XML
	Model trace validation
	UML and OWL complaint
	Multi-format exports – Protégé, Microsoft® Project, or other KBSI tools
	Drag and drop graphical interface

The ModelMosaic® knowledge management toolkit is an intuitive and easy to use technology that allows knowledge engineers to extract, visualize, analyze, and merge ontologies in support of many types of knowledge engineering scenarios. The ModelMosaic® toolkit provides the basis for sustainable knowledge management that encompasses the entire knowledge life cycle, from capture/discovery to representation, analysis, validation, storage, retrieval, delivery, and evolution over extended periods of time.