Following Simon Sinek's inspirational "Why-What-How" rhetoric, we give below—in this order—the motivation, objective, and means of the Constraint Event-Driven Automated Reasoning (CEDAR) Project
Today, the whole world is abuzz about how to manage enormous amounts of data (Big Data); moreover, this data is connected throughout the Internet (Linked Data); its use must be able to extract meaning implicit in the data (Semantic Web); processing this data must take care of the fact that it is distributed (Cloud Computing); therefore, a new technology is emerging for storing and processing such information (Knowledge Bases); all these challenges are keys for endowing software with intelligence (Software Intelligence). However, current standards and technology (adopted before being tested—such as OWL) fail on all counts. Taking up these challenges with adequate working alternatives that are up to the required tasks is the essential motivation for the CEDAR Project.
The CEDAR Project's objective is to offer an effective, efficient, and usable technology that is expressive to represent knowledge, adequate to reason about data, capable of scaling up to enormous amounts of data and handling distributed information, in real time.
The CEDAR Project provides tools and know-how needed to process all knowledge and data as typed labelled graphs that can be naturally formalized as logical constraints, readily made to represent conceptual taxonomies, efficiently used as ontologies providing implicit information, and easily deployable as distributed linked data over the Internet.