Rule‐based Visual Mappings – with a Case Study on Poetry Visualization

In this paper, we present a user‐centered design study on poetry visualization. We develop a rule‐based solution to address the conflicting needs for maintaining the flexibility of visualizing a large set of poetic variables and for reducing the tedium and cognitive load in interacting with the visual mapping control panel. We adopt Munzner's nested design model to maintain high‐level interactions with the end users in a closed loop. In addition, we examine three design options for alleviating the difficulty in visualizing poems latitudinally. We present several example uses of poetry visualization in scholarly research on poetry.

[1]  Martin Wattenberg,et al.  The Word Tree, an Interactive Visual Concordance , 2008, IEEE Transactions on Visualization and Computer Graphics.

[2]  Christopher G. Healey,et al.  Choosing effective colours for data visualization , 1996, Proceedings of Seventh Annual IEEE Visualization '96.

[3]  G. Derringer,et al.  Simultaneous Optimization of Several Response Variables , 1980 .

[4]  Tamara Munzner,et al.  A Nested Model for Visualization Design and Validation , 2009, IEEE Transactions on Visualization and Computer Graphics.

[5]  R. Shepard.  Attention and the metric structure of the stimulus space. , 1964 .

[6]  Jean-Daniel Fekete,et al.  MatrixExplorer: a Dual-Representation System to Explore Social Networks , 2006, IEEE Transactions on Visualization and Computer Graphics.

[7]  Á. Kristjánsson,et al.  In Search of Remembrance: Evidence for Memory in Visual Search , 2000, Psychological science.

[8]  Michael J. McGuffin,et al.  Interactive visualization of genealogical graphs , 2005, IEEE Symposium on Information Visualization, 2005. INFOVIS 2005..

[9]  Catherine Plaisant,et al.  What's being said near “Martha”? Exploring name entities in literary text collections , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[10]  Jacques Bertin,et al.  Semiology of Graphics - Diagrams, Networks, Maps , 2010 .

[11]  Hsinchun Chen,et al.  Categorization and analysis of text in computer mediated communication archives using visualization , 2007, JCDL '07.

[12]  S. Kosslyn.  Image and mind , 1982 .

[13]  Eliane Regina de Almeida Valiati,et al.  A taxonomy of tasks for guiding the evaluation of multidimensional visualizations , 2006, BELIV '06.

[14]  Louise Bogan.  The blue estuaries: Poems, 1923-1968 , 1975 .

[15]  Jean-Daniel Fekete,et al.  Task taxonomy for graph visualization , 2006, BELIV '06.

[16]  M. Sheelagh T. Carpendale,et al.  DocuBurst: Visualizing Document Content using Language Structure , 2009, Comput. Graph. Forum.

[17]  Martin Wattenberg,et al.  Arc diagrams: visualizing structure in strings , 2002, IEEE Symposium on Information Visualization, 2002. INFOVIS 2002..

[18]  Helen Armstrong,et al.  Myopia: A Visualization Tool in Support of Close Reading , 2012, DH.

[19]  John Stasko,et al.  BEST PAPER: A Knowledge Task-Based Framework for Design and Evaluation of Information Visualizations , 2004 .

[20]  John J. Bertin,et al.  The semiology of graphics , 1983 .

[21]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[22]  Pat Hanrahan,et al.  Show Me: Automatic Presentation for Visual Analysis , 2007, IEEE Transactions on Visualization and Computer Graphics.

[23]  D. Booth,et al.  Discriminative feature integration by individuals. , 1993, Acta psychologica.

[24]  Ben Shneiderman,et al.  Discovering interesting usage patterns in text collections: integrating text mining with visualization , 2007, CIKM '07.

[25]  Jeffrey Heer,et al.  Crowdsourcing graphical perception: using mechanical turk to assess visualization design , 2010, CHI.

[26]  Tanya E. Clement,et al.  Sounding for Meaning: Analyzing Aural Patterns Across Large Digital Collections , 2012, DH.

[27]  Franco Moretti.  Graphs, Maps, Trees: Abstract Models for a Literary History , 2005 .

[28]  Martin Wattenberg,et al.  Mapping Text with Phrase Nets , 2009, IEEE Transactions on Visualization and Computer Graphics.

[29]  Finn Årup Nielsen,et al.  A New ANEW: Evaluation of a Word List for Sentiment Analysis in Microblogs , 2011, #MSM.

[30]  Jim Davies,et al.  Taxonomy-Based Glyph Design—with a Case Study on Visualizing Workflows of Biological Experiments , 2012, IEEE Transactions on Visualization and Computer Graphics.

[31]  Colin Ware,et al.  Information Visualization: Perception for Design , 2000 .

[32]  W. Cleveland,et al.  Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods , 1984 .

[33]  Marc R. Plamondon.  Virtual Verse Analysis: Analysing Patterns in Poetry , 2006 .

[34]  Herbert A. Simon,et al.  Why a Diagram is (Sometimes) Worth Ten Thousand Words , 1987, Cogn. Sci..

[35]  Herbert A. Simon,et al.  Why a Diagram is (Sometimes) Worth Ten Thousand Words , 1987 .

[36]  Daniel A. Keim,et al.  Visual evaluation of text features for document summarization and analysis , 2008, 2008 IEEE Symposium on Visual Analytics Science and Technology.

[37]  Daniel A. Keim,et al.  Literature Fingerprinting: A New Method for Visual Literary Analysis , 2007, 2007 IEEE Symposium on Visual Analytics Science and Technology.

[38]  ChenMin,et al.  Taxonomy-Based Glyph Design—with a Case Study on Visualizing Workflows of Biological Experiments , 2012 .