Visual Representations
Identifieur interne : 000D64 ( Istex/Corpus ); précédent : 000D63; suivant : 000D65Visual Representations
Auteurs : Carsten Görg ; Mathias Pohl ; Ermir Qeli ; Kai XuSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Url:
DOI: 10.1007/978-3-540-71949-6_4
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ISTEX:740255227A5FB8DBBF75F496C496C2E582915AEELe document en format XML
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It displays tree topology and nodes sizes Node size is proportional to the angle swept by a node. The tree ring is similar to the information slices</title></host></json:item><json:item><host><author></author><title>Icicle plot, whose node size is proportional to the width of the node. It is similar to the Kleiner and Hartigan's concept of castles</title></host></json:item><json:item><host><author></author><title>Treemap, as discussed above</title></host></json:item><json:item><author></author><host><author></author><title>Visual Representations</title></host></json:item><json:item><host><author></author><title>Determine how many groups are in the network, and separate the four highlighted actors according to different groups</title></host></json:item><json:item><author></author><host><author></author><title>General preference of the drawings</title></host><title>Preference of the crossings regarding completing the tasks</title></json:item><json:item><host><author></author><title>Methods that are based on the force-directed model, such as the GRIP Method [286, 287], the Fast Multi-Scale Method</title></host></json:item><json:item><host><author></author><title>For small graphs, node-link diagrams are always more readable than matri- ces</title></host></json:item><json:item><author></author><host><author></author><title>These topics are addressed in the next subsection</title></host><title>For more complex tasks, such as " path finding " , an appropriate interaction is always preferable, for example, by selecting a node and displaying all the possible paths starting from it and ending at a pointed node. Besides graph size, there are other issues that make graph visualization challenging . Examples include visualizing multiple graphs and node</title></json:item><json:item><host><author></author><title>Integrated Graph Drawing In some applications, it is essential for users to be able to compare different graphs visually. However, well-known techniques, like multiple views or dynamic graph drawing, are not sufficient for this task as they are based on</title></host></json:item></refBibs><genre><json:string>conference</json:string></genre><serie><editor><json:item><name>David Hutchison</name></json:item><json:item><name>Takeo Kanade</name></json:item><json:item><name>Josef Kittler</name></json:item><json:item><name>Jon M. Kleinberg</name></json:item><json:item><name>Friedemann Mattern</name></json:item><json:item><name>John C. Mitchell</name></json:item><json:item><name>Moni Naor</name></json:item><json:item><name>Oscar Nierstrasz</name></json:item><json:item><name>C. Pandu Rangan</name></json:item><json:item><name>Bernhard Steffen</name></json:item><json:item><name>Madhu Sudan</name></json:item><json:item><name>Demetri Terzopoulos</name></json:item><json:item><name>Doug Tygar</name></json:item><json:item><name>Moshe Y. Vardi</name></json:item><json:item><name>Gerhard Weikum</name></json:item></editor><issn><json:string>0302-9743</json:string></issn><language><json:string>unknown</json:string></language><eissn><json:string>1611-3349</json:string></eissn><title>Lecture Notes in Computer Science</title><copyrightDate>2007</copyrightDate></serie><host><editor><json:item><name>Andreas Kerren</name></json:item><json:item><name>Achim Ebert</name></json:item><json:item><name>Jörg Meyer</name></json:item></editor><subject><json:item><value>Computer Science</value></json:item><json:item><value>Computer Science</value></json:item><json:item><value>Image Processing and Computer Vision</value></json:item><json:item><value>Computer Graphics</value></json:item><json:item><value>Pattern Recognition</value></json:item><json:item><value>User Interfaces and Human Computer Interaction</value></json:item><json:item><value>Artificial Intelligence (incl. 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anomalies.</note><note type="content">The understanding of both large-scale as well as small-scale features of data.</note><note type="content">The creation of various hypotheses related to the data.</note><note type="content">Information recording, that is related to the usage of visual presentations as a storage mechanism in order to avoid the need for memorization of data and their relationships.</note><note type="content">Information communication, where visual representations play the role of a message for communicating the essential features of the data visualized.</note><note type="content">Information processing, where visual representations are used as a means to derive knowledge from data.</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">Visual Representations</title><author xml:id="author-1"><persName><forename type="first">Carsten</forename><surname>Görg</surname></persName><affiliation>College of Computing, 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Rangan</surname></persName></editor><editor><persName><forename type="first">Bernhard</forename><surname>Steffen</surname></persName></editor><editor><persName><forename type="first">Madhu</forename><surname>Sudan</surname></persName></editor><editor><persName><forename type="first">Demetri</forename><surname>Terzopoulos</surname></persName></editor><editor><persName><forename type="first">Doug</forename><surname>Tygar</surname></persName></editor><editor><persName><forename type="first">Moshe</forename><forename type="first">Y.</forename><surname>Vardi</surname></persName></editor><editor><persName><forename type="first">Gerhard</forename><surname>Weikum</surname></persName></editor><biblScope><date>2007</date></biblScope><idno type="pISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="series-Id">558</idno></series><idno type="istex">740255227A5FB8DBBF75F496C496C2E582915AEE</idno><idno type="DOI">10.1007/978-3-540-71949-6_4</idno><idno type="ChapterID">4</idno><idno 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Robotics)</BookSubject><SubjectCollection Code="SUCO11645">Computer Science</SubjectCollection></BookSubjectGroup></BookInfo><BookHeader><EditorGroup><Editor><EditorName DisplayOrder="Western"><GivenName>Andreas</GivenName><FamilyName>Kerren</FamilyName></EditorName><Contact><Email>kerren@acm.org</Email></Contact></Editor><Editor><EditorName DisplayOrder="Western"><GivenName>Achim</GivenName><FamilyName>Ebert</FamilyName></EditorName><Contact><Email>ebert@informatik.uni-kl.de</Email></Contact></Editor><Editor><EditorName DisplayOrder="Western"><GivenName>Jörg</GivenName><FamilyName>Meyer</FamilyName></EditorName><Contact><Email>jmeyer@uci.edu</Email></Contact></Editor></EditorGroup></BookHeader><Part ID="Part2"><PartInfo TocLevels="0"><PartID>2</PartID><PartSequenceNumber>2</PartSequenceNumber><PartTitle>Part I. Fundamental Principles and Methods</PartTitle><PartChapterCount>4</PartChapterCount><PartContext><SeriesID>558</SeriesID><BookTitle>Human-Centered Visualization Environments</BookTitle></PartContext></PartInfo><Chapter ID="Chap4" Language="En"><ChapterInfo ChapterType="OriginalPaper" NumberingStyle="Unnumbered" TocLevels="0" ContainsESM="No"><ChapterID>4</ChapterID><ChapterDOI>10.1007/978-3-540-71949-6_4</ChapterDOI><ChapterSequenceNumber>4</ChapterSequenceNumber><ChapterTitle Language="En">Visual Representations</ChapterTitle><ChapterFirstPage>163</ChapterFirstPage><ChapterLastPage>230</ChapterLastPage><ChapterCopyright><CopyrightHolderName>Springer-Verlag Berlin Heidelberg</CopyrightHolderName><CopyrightYear>2007</CopyrightYear></ChapterCopyright><ChapterGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ChapterGrants><ChapterContext><SeriesID>558</SeriesID><PartID>2</PartID><BookID>978-3-540-71949-6</BookID><BookTitle>Human-Centered Visualization Environments</BookTitle></ChapterContext></ChapterInfo><ChapterHeader><AuthorGroup><Author AffiliationIDS="Aff1"><AuthorName DisplayOrder="Western"><GivenName>Carsten</GivenName><FamilyName>Görg</FamilyName></AuthorName></Author><Author AffiliationIDS="Aff2"><AuthorName DisplayOrder="Western"><GivenName>Mathias</GivenName><FamilyName>Pohl</FamilyName></AuthorName></Author><Author AffiliationIDS="Aff3"><AuthorName DisplayOrder="Western"><GivenName>Ermir</GivenName><FamilyName>Qeli</FamilyName></AuthorName></Author><Author AffiliationIDS="Aff4"><AuthorName DisplayOrder="Western"><GivenName>Kai</GivenName><FamilyName>Xu</FamilyName></AuthorName></Author><Affiliation ID="Aff1"><OrgName>College of Computing, Georgia Institute of Technology, Atlanta</OrgName><OrgAddress><Country>USA</Country></OrgAddress></Affiliation><Affiliation ID="Aff2"><OrgName>University of Trier</OrgName><OrgAddress><Country>Germany</Country></OrgAddress></Affiliation><Affiliation ID="Aff3"><OrgName>University of Marburg</OrgName><OrgAddress><Country>Germany</Country></OrgAddress></Affiliation><Affiliation ID="Aff4"><OrgName>National ICT</OrgName><OrgAddress><Country>Australia</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>Visualization can help in the process of extracting insight from data during decision-making. Its advantages are based on the ability to rapidly interpret large quantities of data. The challenge in this context consists in constructing visualization systems which enable the user to understand and perceive the data effectively by providing transparent interaction methods for effective communication between the user and the data. Ware [872] states a number of advantages of visualization, namely:</Para><Para><UnorderedList Mark="Bullet"><ItemContent><Para>The ability to comprehend huge amounts of data.</Para></ItemContent><ItemContent><Para>The perception of properties that are otherwise not anticipated.</Para></ItemContent><ItemContent><Para>The extraction of problems with data itself, i.e., detecting outliers or anomalies.</Para></ItemContent><ItemContent><Para>The understanding of both large-scale as well as small-scale features of data.</Para></ItemContent><ItemContent><Para>The creation of various hypotheses related to the data.</Para></ItemContent></UnorderedList> Visual representations range from simple maps and schematic diagrams to computer generated 2D and 3D visualizations. They differ themselves from other kinds of representations, e.g., sentential representations, in the fact that they make use of <Emphasis Type="Italic">visual variables</Emphasis> to convey the information to the user. In contrast, sentential representations use the semantics of their constituent units, words, and letters, to achieve the same thing. Thus, the meaning of a word is dependent on its context and its letters but not on the spatial position of the word.</Para><Para>The aim of visual representations is dependent on the context of their usage. However, their advantages are usually focused on these three categories [85]: <UnorderedList Mark="Bullet"><ItemContent><Para><Emphasis Type="Italic">Information recording</Emphasis>, that is related to the usage of visual presentations as a storage mechanism in order to avoid the need for memorization of data and their relationships.</Para></ItemContent><ItemContent><Para><Emphasis Type="Italic">Information communication</Emphasis>, where visual representations play the role of a <Emphasis Type="Italic">message</Emphasis> for communicating the essential features of the data visualized.</Para></ItemContent><ItemContent><Para><Emphasis Type="Italic">Information processing</Emphasis>, where visual representations are used as a means to derive knowledge from data.</Para></ItemContent></UnorderedList> Whereas the first two advantages are valid also for other kinds of representations, the last one is specific for visual representations.</Para><Para>This chapter is concerned with visual representations in the context of human-centered visualization environments. Considering the variety of issues that relate to visual representations, it will focus on computer-generated visual representations in different contexts. Before introducing the various techniques which are used to visualize specific data types, a short introduction to perceptual issues is given in Section 4.1. Furthermore, different issues, such as taxonomies for data, visual variables and their ability to express different data types, are discussed in Section 4.1. Section 4.2 focuses on general criteria used in information visualization and the use of metaphors. Section 4.3 presents a survey of different visualization techniques, mainly in the context of multivariate data, by discussing properties of different techniques related to their comprehensive and interaction properties, advantages, and drawbacks with illustrations given for different data sets. Section 4.4 provides an overview of existing evaluations on visualization techniques designed for graphs and trees. The survey mainly focuses on the effect of graph layout algorithms which compute the position of nodes and edges, as well as on user’s understanding of graphs for different tasks. Section 4.5 covers several issues concerning multiple view visualizations. Apart from a classification of multiple view instances, design-issues are discussed. The section is concluded with a comparison based on evaluation studies between multiple views and integrated views.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Visual Representations</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Visual Representations</title></titleInfo><name type="personal"><namePart type="given">Carsten</namePart><namePart type="family">Görg</namePart><affiliation>College of Computing, Georgia Institute of Technology, Atlanta, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Mathias</namePart><namePart type="family">Pohl</namePart><affiliation>University of Trier, Germany</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Ermir</namePart><namePart type="family">Qeli</namePart><affiliation>University of Marburg, Germany</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Kai</namePart><namePart type="family">Xu</namePart><affiliation>National ICT, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2007</dateIssued><copyrightDate encoding="w3cdtf">2007</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><note type="content">The ability to comprehend huge amounts of data.</note><note type="content">The perception of properties that are otherwise not anticipated.</note><note type="content">The extraction of problems with data itself, i.e., detecting outliers or anomalies.</note><note type="content">The understanding of both large-scale as well as small-scale features of data.</note><note type="content">The creation of various hypotheses related to the data.</note><note type="content">Information recording, that is related to the usage of visual presentations as a storage mechanism in order to avoid the need for memorization of data and their relationships.</note><note type="content">Information communication, where visual representations play the role of a message for communicating the essential features of the data visualized.</note><note type="content">Information processing, where visual representations are used as a means to derive knowledge from data.</note><relatedItem type="host"><titleInfo><title>Human-Centered Visualization Environments</title><subTitle>GI-Dagstuhl Research Seminar, Dagstuhl Castle, Germany, March 5-8, 2006, Revised Lectures</subTitle></titleInfo><name type="personal"><namePart type="given">Andreas</namePart><namePart type="family">Kerren</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Achim</namePart><namePart type="family">Ebert</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jörg</namePart><namePart type="family">Meyer</namePart><role><roleTerm type="text">editor</roleTerm></role></name><genre type="book-series" displayLabel="Proceedings"></genre><originInfo><copyrightDate encoding="w3cdtf">2007</copyrightDate><issuance>monographic</issuance></originInfo><subject><genre>Book-Subject-Collection</genre><topic authority="SpringerSubjectCodes" authorityURI="SUCO11645">Computer Science</topic></subject><subject><genre>Book-Subject-Group</genre><topic authority="SpringerSubjectCodes" authorityURI="I">Computer Science</topic><topic authority="SpringerSubjectCodes" authorityURI="I22021">Image Processing and Computer Vision</topic><topic authority="SpringerSubjectCodes" authorityURI="I22013">Computer Graphics</topic><topic authority="SpringerSubjectCodes" authorityURI="I2203X">Pattern Recognition</topic><topic authority="SpringerSubjectCodes" authorityURI="I18067">User Interfaces and Human Computer Interaction</topic><topic authority="SpringerSubjectCodes" authorityURI="I21017">Artificial Intelligence (incl. Robotics)</topic></subject><identifier type="DOI">10.1007/978-3-540-71949-6</identifier><identifier type="ISBN">978-3-540-71948-9</identifier><identifier type="eISBN">978-3-540-71949-6</identifier><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="BookTitleID">149088</identifier><identifier type="BookID">978-3-540-71949-6</identifier><identifier type="BookChapterCount">8</identifier><identifier type="BookVolumeNumber">4417</identifier><identifier type="BookSequenceNumber">4417</identifier><identifier type="PartChapterCount">4</identifier><part><date>2007</date><detail type="part"><title>Part I. Fundamental Principles and Methods</title></detail><detail type="volume"><number>4417</number><caption>vol.</caption></detail><extent unit="pages"><start>163</start><end>230</end></extent></part><recordInfo><recordOrigin>Springer-Verlag Berlin Heidelberg, 2007</recordOrigin></recordInfo></relatedItem><relatedItem type="series"><titleInfo><title>Lecture Notes in Computer Science</title></titleInfo><name type="personal"><namePart type="given">David</namePart><namePart type="family">Hutchison</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Takeo</namePart><namePart type="family">Kanade</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Josef</namePart><namePart type="family">Kittler</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Jon</namePart><namePart type="given">M.</namePart><namePart type="family">Kleinberg</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Friedemann</namePart><namePart type="family">Mattern</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">John</namePart><namePart type="given">C.</namePart><namePart type="family">Mitchell</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Moni</namePart><namePart type="family">Naor</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Oscar</namePart><namePart type="family">Nierstrasz</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">C.</namePart><namePart type="family">Pandu Rangan</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Bernhard</namePart><namePart type="family">Steffen</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Madhu</namePart><namePart type="family">Sudan</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Demetri</namePart><namePart type="family">Terzopoulos</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Doug</namePart><namePart type="family">Tygar</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Moshe</namePart><namePart type="given">Y.</namePart><namePart type="family">Vardi</namePart><role><roleTerm type="text">editor</roleTerm></role></name><name type="personal"><namePart type="given">Gerhard</namePart><namePart type="family">Weikum</namePart><role><roleTerm type="text">editor</roleTerm></role></name><originInfo><copyrightDate encoding="w3cdtf">2007</copyrightDate><issuance>serial</issuance></originInfo><identifier type="ISSN">0302-9743</identifier><identifier type="eISSN">1611-3349</identifier><identifier type="SeriesID">558</identifier><recordInfo><recordOrigin>Springer-Verlag Berlin Heidelberg, 2007</recordOrigin></recordInfo></relatedItem><identifier type="istex">740255227A5FB8DBBF75F496C496C2E582915AEE</identifier><identifier type="DOI">10.1007/978-3-540-71949-6_4</identifier><identifier type="ChapterID">4</identifier><identifier type="ChapterID">Chap4</identifier><accessCondition type="use and reproduction" contentType="copyright">Springer-Verlag Berlin Heidelberg, 2007</accessCondition><recordInfo><recordContentSource>SPRINGER</recordContentSource><recordOrigin>Springer-Verlag Berlin Heidelberg, 2007</recordOrigin></recordInfo></mods></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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