HARVEST is an intelligent visualization system designed to empower everyday business users to derive insight from large amounts of data. It combines three key technologies to support a complex, exploratory visualization-based analysis process without requiring users to be visualization or computer experts. First, HARVEST employs a set of smart visual analytic widgets that can be easily reused across applications and support incremental visual updates as required by a continuous visual analytic process. Second, it has a visualization recommendation engine that dynamically suggests suit- able visualization widgets to users in context. Third, it supports the semantics-based capture of user visual analytic activity for the reuse and sharing of insight provenance.
HARVEST also provides integrated text analysis services that users to easily upload a document collection, select a set of properties to extract, and visualize statistical summaries of the extracted information. The system also allows users to upload structured and semi-structured data, making it possible for non-experts to perform sophisticated analyses that explore the relationships between structured properties and data properties extracted via text mining.
David Gotz, Zhen Wen, Jie Lu, Peter Kissa, Nan Cao, Wei Hong Qian, Shi Xia Liu, and Michelle X. Zhou. HARVEST: An Intelligent Visual Analytic Tool for the Masses. ACM IUI 2010 International Workshop on Intelligent Visual Interfaces for Text Analysis, Hong Kong, China (2010).
David Gotz, Zhen Wen, Jie Lu, Peter Kissa, Michelle X. Zhou, Nan Cao, Wei Hong Qian, and Shi Xia Lui. HARVEST – Visualization and Analysis for the Masses. IEEE Information Visualization Poster, Columbus, Ohio (2008).