Configurable Object Schema

About

Inventors from the Georgia Tech Research Institute have created a domain tolerant, yet domain aware, approach to data modelling and decomposition with a method called Configurable Hyper-referenced Associative Object Schema (CHAOS). This invention is intended for use in the Multi-domain Analysis and Deep Knowledge Association Toolkit (MADKAT), a GTRI Internal Research and Development (IRAD) project for analytic discovery in massive multi-source and multi-domain data sets. CHAOS is a lightweight decomposition schema for unstructured and structured data to provide extract, transform, and load (ETL) capabilities needed for MADKAT. Due to the human-centered nature of the MADKAT project, an overarching goal of CHAOS is to be comprehensible to the target audience and provide continual self-documentation of purpose. This means that underlying data representations should always explicitly state their identity and purpose while also serving their function of maintaining complex knowledge relationships. This allows the decomposition of data to follow logically from the CHAOS structures and provides traceability through the resultant representation. Potential Commercial Applications: Business-business development, conflict of interest, market research, market segmentation Computing - data warehousing, search engine, analytic platform Legal - patent research, conflict of interest, compliance audit Health Informatics - health database aggregation Defense/Law Enforcement - investigation, sensor data fusion Benefits/Advantages: Efficient application of tools and algorithms Simplifies the extract, load, and transform phase of data processing