國立虎尾科技大學 |

Targeting Designs of Scalable, Exploratory Summary Visualizations.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Targeting Designs of Scalable, Exploratory Summary Visualizations./
作者:	Sarikaya, Alper T.
面頁冊數:	1 online resource (191 pages)
附註:	Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Contained By:	Dissertation Abstracts International78-12B(E).
標題:	Computer science. -
電子資源:	click for full text (PQDT)
ISBN:	9780355227949

Targeting Designs of Scalable, Exploratory Summary Visualizations.
Sarikaya, Alper T.

Targeting Designs of Scalable, Exploratory Summary Visualizations. - 1 online resource (191 pages)

Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.

Thesis (Ph.D.)--The University of Wisconsin - Madison, 2017.

Includes bibliographical references

Data visualization provides a human-digestible interface to digital data. With increasing data volumes and increased complexity and interrelationships, so have the demands on supporting effective visualization to support this interface. With complex data at scale, it becomes necessary to summarize the data in some manner to communicate high-level information of a dataset, such as distributions, trends, or anomalies. By the nature of summarization, fidelity in the visual representation of such summaries is reduced. With summarized data, visualization designs must make trade-offs to support particular types of tasks and analyses over others. In this dissertation, I present organizations and applications for the effective design of summary visualizations. Organizations of summary visualization identify the relevant factors that affect appropriate design, such as the method of summarizing data, the analysis goals and tasks of the viewer, and the characteristics of the data. Applications of summary visualizations demonstrate the holistic application of appropriate design decisions to support the analysis of complex scientific data. These factors are linked together to identify appropriate design strategies and highlight open problems for the effective design of visualization. Through this research presented herein, I provide new guidance for effective visualization of collections of data, allowing for the wider dissemination and analysis of complex data.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355227949Subjects--Topical Terms:

573171
Computer science.
Index Terms--Genre/Form:

554714
Electronic books.

Targeting Designs of Scalable, Exploratory Summary Visualizations.
LDR:02710ntm a2200337Ki 4500 001 919426
005 20181127125341.5
006 m o u
007 cr mn||||a|a||
008 190606s2017 xx obm 000 0 eng d
020 $a 9780355227949
035 $a (MiAaPQ)AAI10623478
035 $a (MiAaPQ)wisc:14820
035 $a AAI10623478
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Sarikaya, Alper T. $3 1194002
245 1 0 $a Targeting Designs of Scalable, Exploratory Summary Visualizations.
264 0 $c 2017
300 $a 1 online resource (191 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
500 $a Adviser: Michael L. Gleicher.
502 $a Thesis (Ph.D.)--The University of Wisconsin - Madison, 2017.
504 $a Includes bibliographical references
520 $a Data visualization provides a human-digestible interface to digital data. With increasing data volumes and increased complexity and interrelationships, so have the demands on supporting effective visualization to support this interface. With complex data at scale, it becomes necessary to summarize the data in some manner to communicate high-level information of a dataset, such as distributions, trends, or anomalies. By the nature of summarization, fidelity in the visual representation of such summaries is reduced. With summarized data, visualization designs must make trade-offs to support particular types of tasks and analyses over others. In this dissertation, I present organizations and applications for the effective design of summary visualizations. Organizations of summary visualization identify the relevant factors that affect appropriate design, such as the method of summarizing data, the analysis goals and tasks of the viewer, and the characteristics of the data. Applications of summary visualizations demonstrate the holistic application of appropriate design decisions to support the analysis of complex scientific data. These factors are linked together to identify appropriate design strategies and highlight open problems for the effective design of visualization. Through this research presented herein, I provide new guidance for effective visualization of collections of data, allowing for the wider dissemination and analysis of complex data.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Computer science. $3 573171
650 4 $a Geography. $3 654331
655 7 $a Electronic books. $2 local $3 554714
690 $a 0984
690 $a 0366
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a The University of Wisconsin - Madison. $b Computer Sciences. $3 1179878
773 0 $t Dissertation Abstracts International $g 78-12B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10623478 $z click for full text (PQDT)