Title:
Informing design of visual analytics systems for intelligence analysis: understanding users, user tasks, and tool usage

Simple item page
dc.contributor.advisor Stasko, John T.
dc.contributor.author Kang, Youn Ah en_US
dc.contributor.committeeMember Foley, James
dc.contributor.committeeMember Grinter, Rebecca
dc.contributor.committeeMember North, Chris
dc.contributor.committeeMember Scholtz, Jean
dc.contributor.department Computing en_US
dc.date.accessioned 2012-09-20T18:22:16Z
dc.date.available 2012-09-20T18:22:16Z
dc.date.issued 2012-07-02 en_US
dc.description.abstract Visual analytics, defined as "the science of analytical reasoning facilitated by interactive visual interfaces," emerged several years ago as a new research field. While it has seen rapid growth for its first five years of existence, the main focus of visual analytics research has been on developing new techniques and systems rather than identifying how people conduct analysis and how visual analytics tools can help the process and the product of sensemaking. The intelligence analysis community in particular has not been fully examined in visual analytics research even though intelligence analysts are one of the major target users for which visual analytics systems are built. The lack of understanding about how analysts work and how they can benefit from visual analytics systems has created a gap between tools being developed and real world practices. This dissertation is motivated by the observation that existing models of sensemaking/intelligence analysis do not adequately characterize the analysis process and that many visual analytics tools do not truly meet user needs and are not being used effectively by intelligence analysts. I argue that visual analytics research needs to adopt successful HCI practices to better support user tasks and add utility to current work practices. As the first step, my research aims (1) to understand work processes and practices of intelligence analysts and (2) to evaluate a visual analytics system in order to identify where and how visual analytics tools can assist. By characterizing the analysis process and identifying leverage points for future visual analytics tools through empirical studies, I suggest a set of design guidelines and implications that can be used for both designing and evaluating future visual analytics systems. en_US
dc.description.degree PhD en_US
dc.identifier.uri http://hdl.handle.net/1853/44847
dc.publisher Georgia Institute of Technology en_US
dc.subject Sensemaking en_US
dc.subject Visual analytics en_US
dc.subject User studies en_US
dc.subject.lcsh Intelligence service Computer network resources
dc.subject.lcsh Reasoning
dc.title Informing design of visual analytics systems for intelligence analysis: understanding users, user tasks, and tool usage en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Stasko, John T.
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Interactive Computing
local.relation.ispartofseries Doctor of Philosophy with a Major in Human-Centered Computing
relation.isAdvisorOfPublication 915f1577-d445-49b2-aa51-02218153f559
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication aac3f010-e629-4d08-8276-81143eeaf5cc
relation.isSeriesOfPublication c9333007-dfa1-4e61-9b38-517b1a4b7c9a
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
kang_youn_a_201208_phd.pdf
Size:
8.24 MB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Theses and Dissertations