Abstract: The present invention extends to methods, systems, and computer program products for developing an item data model for an item. Aspects of the invention can automate the process of data collection of “facts” for “items” that information is needed about. Facts can be organized and normalized to eliminate redundant facts, and interpret what is found. Data requirements extraction and automated modeling using a combination of data virtualization, data analytics, extract, transform, and load (ETL), web crawlers, and reverse engineering systems, can be used along with other technologies to develop an item model. A model owner feeds a curating module with the information for locating the facts to be used, and initiating the modeling process. Existing data structures, websites, vendor input, etc. can be described to the import process, and an item model is produced. The model can be imported into existing modeling tools for viewing, or viewed as XML.

Abstract: The present invention extends to methods, systems, and computer program products for developing an item data model for an item. Aspects of the invention can automate the process of data collection of “facts” for “items” that information is needed about. Facts can be organized and normalized to eliminate redundant facts, and interpret what is found. Data requirements extraction and automated modeling using a combination of data virtualization, data analytics, extract, transform, and load (ETL), web crawlers, and reverse engineering systems, can be used along with other technologies to develop an item model. A model owner feeds a curating module with the information for locating the facts to be used, and initiating the modeling process. Existing data structures, websites, vendor input, etc. can be described to the import process, and an item model is produced. The model can be imported into existing modeling tools for viewing, or viewed as XML.

Abstract: A system is provided that implements a more systematic process for obtaining business knowledge that is more efficient and timely. The process automatically reads business documents and produces a business ontology. In one implementation, the process dissects documents into sentences or collection of words that most resembles a sentence. Natural language processing algorithms may be used to identify the role of term within a sentence. Terms and associations resulting from the document analysis are used to specify a business ontology which can be then used to provide input to a software design process, among other business uses.

Abstract: A system is provided that implements a more systematic process for obtaining business knowledge that is more efficient and timely. The process automatically reads business documents and produces a business ontology. In one implementation, the process dissects documents into sentences or collection of words that most resembles a sentence. Natural language processing algorithms may be used to identify the role of term within a sentence. Terms and associations resulting from the document analysis are used to specify a business ontology which can be then used to provide input to a software design process, among other business uses.