Information-centric representation is a method of modeling real world concepts, entities, and phenomena in a computer's virtual environment. Unlike traditional data-oriented representation, which focuses on representing unstructured data (i.e., unstructured words and/or numbers) in a virtual environment, information-centric representation focuses on representing the defining attributes and the grammatic relationships—the context—that elevate unstructured data into meaningful information in a computing environment.
Graphical comparison of unstructured data, structured information, and knowledge-based inferences.
By facilitating the representation of contextual information, information-centric representation enables the application of intelligent computer programs known as software agents (see Intelligent & Adaptive Tools) in software systems. These agents monitor, analyze, and reason about digital information, providing, thereby, extensive and tireless support to human decision-makers.
Information representation involving ontologies. Emphasis on coding language requirements, including conceptual distance, expressive power, standards compliance, translatability, formal semantics, and flexibility.
Dynamic extension and merging of ontologies. Emphasis on structuring ontologies so that they can progressively evolve during the operation of information systems. For example, structuring a high-level core ontology (i.e., an ontology that represents general concepts and notions) so that it can refine its granularity into a biased and far more detailed application-specific ontology.