AN EXTENDABLE VISUALIZATION AND USER INTERFACE DESIGN FOR TIME-VARYING MULTIVARIATE GEOSCIENCE DATA

Authors

Yanfu Zhou, University of Nebraska - LincolnFollow

Date of this Version

Summer 8-2016

Document Type

Article

Citation

Zhou, Y., 2016, An Extendable Visualization and User Interaction Design For Time-varying Multivariate Geoscience Data (Master's Thesis). DigitalCommons@University of Nebraska-Lincoln.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Computer Science, Under the Supervision of Professor Hongfeng Yu. Lincoln, Nebraska: August, 2016

Copyright (c) 2016 Yanfu Zhou

Abstract

Geoscience data has unique and complex data structures, and its visualization has been challenging due to a lack of effective data models and visual representations to tackle the heterogeneity of geoscience data. In today’s big data era, the needs of visualizing geoscience data become urgent, especially driven by its potential value to human societies, such as environmental disaster prediction, urban growth simulation, and so on. In this thesis, I created a novel geoscience data visualization framework and applied interface automata theory to geoscience data visualization tasks. The framework can support heterogeneous geoscience data and facilitate data operations. The interface automata can generate a series of interactions that can efficiently impress users, which also provides an intuitive method for visualizing and analysis geoscience data. Except clearly guided users to the specific visualization, interface automata can also enhance user experience by eliminating automation surprising, and the maintenance overhead is also reduced. The new framework was applied to INSIGHT, a scientific hydrology visualization and analysis system that was developed by the Nebraska Department of Natural Resources (NDNR). Compared to the existing INSIGHT solution, the new framework has brought many advantages that do not exist in the existing solution, which proved that the framework is efficient and extendable for visualizing geoscience data.

Adviser: Hongfeng Yu