Foundations of data visualization:
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 discours...
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| Weitere Verfasser: | , , |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2020]
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| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | 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 |
| Beschreibung: | 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 |
| Beschreibung: | xvii, 389 Seiten Illustrationen, Diagramme 776 grams |
| ISBN: | 9783030344436 9783030344467 |
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| 500 | |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 | ||
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Datensatz im Suchindex
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|---|---|
| adam_text | Contents Part I Theoretical Underpinnings of Data Visualization 1 The Fabric of Visualization....................................................................... G. Elisabeta Marai and Torsten Möller 5 2 Visual Abstraction ..................................................................................... Ivan Viola, Min Chen, and Tobias Isenberg 15 3 Measures in Visualization Space............................................................. Fabian Bolte and Stefan Bruckner 39 4 Knowledge-Assisted Visualization and Guidance.................................. Silvia Miksch, Heike Leitte, and Min Chen 61 5 Mathematical Foundations in Visualization.......................................... Ingrid Hotz, Roxana Bujack, Christoph Garth, and Bei Wang 87 6 Transformations, Mappings, and Data Summaries............................ Ross Whitaker and Ingrid Hotz 121 Part II 7 Empirical Studies in Visualization A Survey of Variables Used in Empirical Studies for Visualization................................................................................. Alfie Abdul-Rahman, Min Chen, and David H. Laidlaw 161 8 Empirical Evaluations with Domain Experts ...................................... Krešimir Matkovič, Thomas Wischgoll, and David H. Laidlaw 9 Evaluation of Visualization Systems with Long-Term Case Studies................................................................................................. Bernhard Preim and Alark Joshi 10 181 195 Vis4Vis: Visualization for (Empirical) Visualization Research .... 209 Daniel Weiskopf xiii
xiv Contents 11 “Isms” in Visualization............................................................................. 225 Min Chen and Darren J. Edwards 12 Open Challenges in Empirical Visualization Research.................... Caroline Ziemkiewicz, Min Chen, David H. Laidlaw, Bernhard Preim, and Daniel Weiskopf Part ПІ 243 Collaboration with Domain Experts 13 Case Studies for Working with Domain Experts................................. Johanna Beyer, Charles Hansen, Mario Hlawitschka, Ingrid Hotz, Barbora Kozlíkova, Gerik Scheuermann, Markus Stommel, Marc Streit, Johannes Waschke, Thomas Wischgoll, and Yong Wan 14 Collaborations Between Industry and University............................... 279 Daniela Oelke and Ariane Sutor 15 Collaborating Successfully with Domain Experts............................... 285 Mario Hlawitschka, Gerik Scheuermann, Christian Blecha, Marc Streit, and Amitabh Varshney Part ГѴ 255 Developing Visualizations for Broad Audiences 16 Reflections on Visualization for Broad Audiences............................... 297 Michael Böttinger, Helen-Nicole Kostis, Maria Velez-Rojas, Penny Rheingans, and Anders Ynnerman 17 Reaching Broad Audiences from a Research Institute Setting......... Michael Böttinger 307 18 Reaching Broad Audiences from a Large Agency Setting................ Helen-Nicole Kostis, Miguel O. Roman, Virginia Kalb, Eleanor C. Stokes, Ranjay Μ. Shrestha, Zhuosen Wang, Lori Schultz, Qingsong Sun, Jordan Bell, Andrew Molthan, Ryan Boiler, and Assaf Anyamba 319 19 Reaching Broad Audiences from a Science Center or Museum
Setting............................................................................ Anders Ynnerman, Patric Ljung, and Alexander Bock 341 20 Reaching Broad Audiences in an Educational Setting........................ 365 Penny Rheingans, Helen-Nicole Kostis, Paulo A. Oemig, Geraldine B. Robbins, and Anders Ynnerman 21 Challenges and Open Issues in Visualization for Broad Audiences.......................................................................... Michael Böttinger, Helen-Nicole Kostis, and Anders Ynnermann 381
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| adam_txt |
Contents Part I Theoretical Underpinnings of Data Visualization 1 The Fabric of Visualization. G. Elisabeta Marai and Torsten Möller 5 2 Visual Abstraction . Ivan Viola, Min Chen, and Tobias Isenberg 15 3 Measures in Visualization Space. Fabian Bolte and Stefan Bruckner 39 4 Knowledge-Assisted Visualization and Guidance. Silvia Miksch, Heike Leitte, and Min Chen 61 5 Mathematical Foundations in Visualization. Ingrid Hotz, Roxana Bujack, Christoph Garth, and Bei Wang 87 6 Transformations, Mappings, and Data Summaries. Ross Whitaker and Ingrid Hotz 121 Part II 7 Empirical Studies in Visualization A Survey of Variables Used in Empirical Studies for Visualization. Alfie Abdul-Rahman, Min Chen, and David H. Laidlaw 161 8 Empirical Evaluations with Domain Experts . Krešimir Matkovič, Thomas Wischgoll, and David H. Laidlaw 9 Evaluation of Visualization Systems with Long-Term Case Studies. Bernhard Preim and Alark Joshi 10 181 195 Vis4Vis: Visualization for (Empirical) Visualization Research . 209 Daniel Weiskopf xiii
xiv Contents 11 “Isms” in Visualization. 225 Min Chen and Darren J. Edwards 12 Open Challenges in Empirical Visualization Research. Caroline Ziemkiewicz, Min Chen, David H. Laidlaw, Bernhard Preim, and Daniel Weiskopf Part ПІ 243 Collaboration with Domain Experts 13 Case Studies for Working with Domain Experts. Johanna Beyer, Charles Hansen, Mario Hlawitschka, Ingrid Hotz, Barbora Kozlíkova, Gerik Scheuermann, Markus Stommel, Marc Streit, Johannes Waschke, Thomas Wischgoll, and Yong Wan 14 Collaborations Between Industry and University. 279 Daniela Oelke and Ariane Sutor 15 Collaborating Successfully with Domain Experts. 285 Mario Hlawitschka, Gerik Scheuermann, Christian Blecha, Marc Streit, and Amitabh Varshney Part ГѴ 255 Developing Visualizations for Broad Audiences 16 Reflections on Visualization for Broad Audiences. 297 Michael Böttinger, Helen-Nicole Kostis, Maria Velez-Rojas, Penny Rheingans, and Anders Ynnerman 17 Reaching Broad Audiences from a Research Institute Setting. Michael Böttinger 307 18 Reaching Broad Audiences from a Large Agency Setting. Helen-Nicole Kostis, Miguel O. Roman, Virginia Kalb, Eleanor C. Stokes, Ranjay Μ. Shrestha, Zhuosen Wang, Lori Schultz, Qingsong Sun, Jordan Bell, Andrew Molthan, Ryan Boiler, and Assaf Anyamba 319 19 Reaching Broad Audiences from a Science Center or Museum
Setting. Anders Ynnerman, Patric Ljung, and Alexander Bock 341 20 Reaching Broad Audiences in an Educational Setting. 365 Penny Rheingans, Helen-Nicole Kostis, Paulo A. Oemig, Geraldine B. Robbins, and Anders Ynnerman 21 Challenges and Open Issues in Visualization for Broad Audiences. Michael Böttinger, Helen-Nicole Kostis, and Anders Ynnermann 381 |
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| id | DE-604.BV046867459 |
| illustrated | Illustrated |
| index_date | 2024-07-03T15:14:40Z |
| indexdate | 2024-07-10T08:56:01Z |
| institution | BVB |
| isbn | 9783030344436 9783030344467 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032276008 |
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| physical | xvii, 389 Seiten Illustrationen, Diagramme 776 grams |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Springer |
| record_format | marc |
| spelling | Foundations of data visualization Min Chen, Helwig Hauser, Penny Rheingans, Gerik Scheuermann, editors Cham Springer [2020] xvii, 389 Seiten Illustrationen, Diagramme 776 grams txt rdacontent n rdamedia nc rdacarrier 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 bicssc bisacsh Optical data processing User interfaces (Computer systems) Mathematics Visualization Computer science Computergrafik (DE-588)4010450-3 gnd rswk-swf Visualisierung (DE-588)4188417-6 gnd rswk-swf Optische Datenverarbeitung (DE-588)4172661-3 gnd rswk-swf Benutzeroberfläche (DE-588)4131424-4 gnd rswk-swf Hardcover, Softcover / Informatik, EDV/Anwendungs-Software Computergrafik (DE-588)4010450-3 s Visualisierung (DE-588)4188417-6 s Optische Datenverarbeitung (DE-588)4172661-3 s Benutzeroberfläche (DE-588)4131424-4 s DE-604 Chen, Min 1960- (DE-588)121504298 edt Hauser, Helwig 1971- (DE-588)133731278 edt Rheingans, Penny (DE-588)1243685514 edt Scheuermann, Gerik 1970- Sonstige (DE-588)121780848 oth Erscheint auch als Online-Ausgabe 978-3-030-34444-3 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032276008&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Foundations of data visualization bicssc bisacsh Optical data processing User interfaces (Computer systems) Mathematics Visualization Computer science Computergrafik (DE-588)4010450-3 gnd Visualisierung (DE-588)4188417-6 gnd Optische Datenverarbeitung (DE-588)4172661-3 gnd Benutzeroberfläche (DE-588)4131424-4 gnd |
| subject_GND | (DE-588)4010450-3 (DE-588)4188417-6 (DE-588)4172661-3 (DE-588)4131424-4 |
| title | Foundations of data visualization |
| title_auth | Foundations of data visualization |
| title_exact_search | Foundations of data visualization |
| title_exact_search_txtP | Foundations of data visualization |
| title_full | Foundations of data visualization Min Chen, Helwig Hauser, Penny Rheingans, Gerik Scheuermann, editors |
| title_fullStr | Foundations of data visualization Min Chen, Helwig Hauser, Penny Rheingans, Gerik Scheuermann, editors |
| title_full_unstemmed | Foundations of data visualization Min Chen, Helwig Hauser, Penny Rheingans, Gerik Scheuermann, editors |
| title_short | Foundations of data visualization |
| title_sort | foundations of data visualization |
| topic | bicssc bisacsh Optical data processing User interfaces (Computer systems) Mathematics Visualization Computer science Computergrafik (DE-588)4010450-3 gnd Visualisierung (DE-588)4188417-6 gnd Optische Datenverarbeitung (DE-588)4172661-3 gnd Benutzeroberfläche (DE-588)4131424-4 gnd |
| topic_facet | bicssc bisacsh Optical data processing User interfaces (Computer systems) Mathematics Visualization Computer science Computergrafik Visualisierung Optische Datenverarbeitung Benutzeroberfläche |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032276008&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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