國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Foundations of data visualization

Chen, Min.

Foundations of data visualization

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Foundations of data visualizationedited by Min Chen ... [et al.].
其他作者:	Chen, Min.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	xvii, 389 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Information visualization.
電子資源:	https://doi.org/10.1007/978-3-030-34444-3
ISBN:	9783030344443$q(electronic bk.)

Foundations of data visualization
Foundations of data visualization[electronic resource] /edited by Min Chen ... [et al.]. - Cham :Springer International Publishing :2020. - xvii, 389 p. :ill., digital ;24 cm.

Part I: Theoretical Underpinnings of Data Visualization -- The Fabric of Visualization -- Visual Abstraction -- Measures in Visualization Space -- Knowledge-Assisted Visualization and Guidance -- Mathematical Foundations in Visualizations -- Transformations, Mappings and Data Summaries -- Part II: Empirical Studies in Visualization -- A Survey of Variables Used in Empirical Studies for Visualization -- Empirical Evaluations with Domain Experts -- Evaluation of Visualization Systems with Long-term Case Studies -- Vis4Vis: Visualization for (Empirical) Visualization Research -- 'Isms' in Visualization -- Open Challenges in Empirical Visualization Research -- Part III: Collaboration with Domain Experts -- Case Studies for Working with Domain Experts -- Collaboration Between Industry and University -- Collaborating Successfully with Domain Experts -- Part IV: Developing Visualizations for Broad Audiences -- Reflections on Visualization for Broad Audiences -- Reaching Broad Audiences from a Research Institute Setting -- Reaching Broad Audiences from a Large Agency Setting -- Reaching Broad Audiences from a Science Center or Museum Setting -- Reaching Broad Audiences in an Educational Setting -- Challenges and Open Issues in Visualization for Broad Audiences.

This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization. Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.

ISBN: 9783030344443$q(electronic bk.)

Standard No.: 10.1007/978-3-030-34444-3doiSubjects--Topical Terms:

248886
Information visualization.

LC Class. No.: QA76.9.I52

Dewey Class. No.: 001.4226

Foundations of data visualization
LDR:04114nmm a2200325 a 4500 001 585094
003 DE-He213
005 20200811170648.0
006 m d
007 cr nn 008maaau
008 210311s2020 sz s 0 eng d
020 $a 9783030344443$q(electronic bk.)
020 $a 9783030344436$q(paper)
024 7 $a 10.1007/978-3-030-34444-3 $2 doi
035 $a 978-3-030-34444-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.I52
072 7 $a UYQV $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYQV $2 thema
082 0 4 $a 001.4226 $2 23
090 $a QA76.9.I52 $b F771 2020
245 0 0 $a Foundations of data visualization $h [electronic resource] / $c edited by Min Chen ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xvii, 389 p. : $b ill., digital ; $c 24 cm.
505 0 $a Part I: Theoretical Underpinnings of Data Visualization -- The Fabric of Visualization -- Visual Abstraction -- Measures in Visualization Space -- Knowledge-Assisted Visualization and Guidance -- Mathematical Foundations in Visualizations -- Transformations, Mappings and Data Summaries -- Part II: Empirical Studies in Visualization -- A Survey of Variables Used in Empirical Studies for Visualization -- Empirical Evaluations with Domain Experts -- Evaluation of Visualization Systems with Long-term Case Studies -- Vis4Vis: Visualization for (Empirical) Visualization Research -- 'Isms' in Visualization -- Open Challenges in Empirical Visualization Research -- Part III: Collaboration with Domain Experts -- Case Studies for Working with Domain Experts -- Collaboration Between Industry and University -- Collaborating Successfully with Domain Experts -- Part IV: Developing Visualizations for Broad Audiences -- Reflections on Visualization for Broad Audiences -- Reaching Broad Audiences from a Research Institute Setting -- Reaching Broad Audiences from a Large Agency Setting -- Reaching Broad Audiences from a Science Center or Museum Setting -- Reaching Broad Audiences in an Educational Setting -- Challenges and Open Issues in Visualization for Broad Audiences.
520 $a This is the first book that focuses entirely on the fundamental questions in visualization. Unlike other existing books in the field, it contains discussions that go far beyond individual visual representations and individual visualization algorithms. It offers a collection of investigative discourses that probe these questions from different perspectives, including concepts that help frame these questions and their potential answers, mathematical methods that underpin the scientific reasoning of these questions, empirical methods that facilitate the validation and falsification of potential answers, and case studies that stimulate hypotheses about potential answers while providing practical evidence for such hypotheses. Readers are not instructed to follow a specific theory, but their attention is brought to a broad range of schools of thoughts and different ways of investigating fundamental questions. As such, the book represents the by now most significant collective effort for gathering a large collection of discourses on the foundation of data visualization. Data visualization is a relatively young scientific discipline. Over the last three decades, a large collection of computer-supported visualization techniques have been developed, and the merits and benefits of using these techniques have been evidenced by numerous applications in practice. These technical advancements have given rise to the scientific curiosity about some fundamental questions such as why and how visualization works, when it is useful or effective and when it is not, what are the primary factors affecting its usefulness and effectiveness, and so on. This book signifies timely and exciting opportunities to answer such fundamental questions by building on the wealth of knowledge and experience accumulated in developing and deploying visualization technology in practice.
650 0 $a Information visualization. $3 248886
650 1 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 274492
650 2 4 $a User Interfaces and Human Computer Interaction. $3 274517
650 2 4 $a Visualization. $3 182994
700 1 $a Chen, Min. $3 680255
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-030-34444-3
950 $a Computer Science (SpringerNature-11645)