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Virginia Tech

Towards Support of Visual Analytics for Synthetic Information

Abstract

dc:description.abstract

This thesis describes a scalable system for visualizing and exploring global synthetic populations. The implementation described in this thesis addresses the following existing limitations of the Syn- thetic Information Viewer (SIV): (i) it adds ability to support synthetic populations for the entire globe by resolving data inconsistencies, (ii) introduces opportunities to explore and find patterns in the data, and (iii) allows the addition of new synthetic population centers with minimal effort. We propose the following extensions to the system: (i) Data Registry: an abstraction layer for handling heterogeneity of data across countries, and adding new population centers for visualizations, and (ii) Visual Query Interface: for exploring and analyzing patterns to gain insights. With these additions, our system is capable of visual exploration and querying of heterogeneous, temporal, spatial and social data for 14 countries with a total population of 830 million. Work in this thesis takes a step towards providing visual analytics capability for synthetic information. This system will assist urban planners, public health analysts, and, any individuals interested in socially-coupled systems, by empowering them to make informed decisions through exploration of synthetic information.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Computer Science and Applications
Department dc:contributor.department
Computer Science
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Agashe, Aditya Vidyanand
Chair dc:contributor.committeechair
  • Marathe, Madhav Vishnu
Committee members dc:contributor.committeemember
  • Fox, Edward A.
  • Bisset, Keith R.
  • Mortveit, Henning S.

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:6026
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/56565

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Agashe, Aditya Vidyanand. Towards Support of Visual Analytics for Synthetic Information. masters thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/56565