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projects:year1:12.4

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12.4 - Visualization of Multivariate Spatiotemporal Data

Project - Summary

Objectives:

  1. Develop an integrated and extensible process and a series of prototypes for gap analytics, portfolio analysis, competitive intelligence surveillance, and large-scale longitudinal evaluative assessments across heterogeneous data sources and a variety of units of analysis over time
  2. Design and develop innovative and robust algorithms to support a flexible workflow of gap analytic tasks, including modeling dynamic high-dimensional data in terms of visualizations of fitness landscapes, identifying and tracking critical paths over fitness landscapes, and analyzing the dynamics of trajectories and other indicators of a complex adaptive system
  3. An extensible and adaptive platform will be built to demonstrate applications in 2~3 priority domains based on recommendations of industry partners and available data sources

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Carolina Cruz-Neira PI Not available Not available UL Lafayette
Dirk Reiners Co-PI Not available Not available UL Lafayette
Dimitri Perkins Researcher Not available Not available UL Lafayette
Xia Lin Researcher Not available Not available Drexel University
Tony Grubessic Researcher Not available Not available Drexel University
Murali Krishna Pusala Graduate Student Not available Not available UL Lafayette

Project - Impact and Uses/Benefits

Three dimensional fitness landscapes provide intuitive representations of potentially complex situations. Such representations provide the basis to which additional information concerning the performance of an organization can be superimposed. Users will benefit from the intuitive and informative representations. Furthermore, providing a stable framework that enables many more functionalities for gap analytic tasks.

Project - Deep Dive

Project - Documents

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projects/year1/12.4.1566425073.txt.gz · Last modified: 2019/08/21 17:04 by sally.johnson