STTR Phase I: Integrating Online Analytical Processing (OLAP) and Ontologies to Discover Inconsistencies in Expectations for Supply and Demand

Clados Management Llc, San Mateo CA

Investigators

Abstract

This Small Business Technology Transfer (STTR) Phase I project aims to produce a software application that enables business people to dramatically improve their ability to forecast supply and demand. In collaboration with the Knowledge Modeling Group at Stanford Medical Informatics, Clados proposes a joint effort to produce relevant aggregation to investigate supply and demand. The effort will proceed in three stages: (1) Capture interactions in OWL from a "training" set of investment research reports; (2) Produce meaningful Online Analytical Processing (OLAP) aggregations on all interactions using the OWL representation directly; and, (3) Evaluate the results by capturing and aggregating interactions from a "control" set of reports. Business people focus heavily on composing narratives to gauge potential supply and demand to guide their investment decisions. In recent years, society has benefited from dramatic increases in volume and availability of information that business people find useful in composing these narratives. However, most people compose those narratives using only the most general tools, predominantly prose documents and spreadsheet tables, and these are insufficient to structure such volume. As a result, society has an opportunity to further improve resource allocation. OLAP technologies may dramatically improve the process of composing narratives to gauge potential supply and demand.