Robert Kosara, Helwig Hauser 1InfoVis STAR The State of the Art in Information Visualization Robert Kosara, Helwig Hauser

2InfoVis STAR Overview Taxonomy Interaction Method Types  1D Methods  2D Methods  nD Methods  Trees InfoVis and SciVis User Studies Future of InfoVis  Networks/Graphs  Temporal Data  Text  Software

Robert Kosara, Helwig Hauser 3InfoVis STAR Taxonomy Most important and most difficult problem The classic: Shneiderman:VL:1996 Problems:  Primarily targets data types (not tasks!)  Mixes data and visual dimensions (cone trees are 3D?!)  Strange classifications (text is 1D?!)  Does not account for use of visualization  A different taxonomy is needed

Robert Kosara, Helwig Hauser 4InfoVis STAR Other Taxonomies There are others...  Operator interaction framework (Chi:InfoVis:1998)  sdf

Robert Kosara, Helwig Hauser 5InfoVis STAR Our Taxonomy Oriented at use of the data  Presentation of the data  How people work with the method  Available interaction methods One method possibly in several categories

Robert Kosara, Helwig Hauser 6InfoVis STAR Interaction Focus+Context (F+C)  Distortion-oriented  Magic lenses/Toolglasses  In-Place  A general(ly good) idea Multiple Views Linking&Brushing (L&B)

Robert Kosara, Helwig Hauser 7InfoVis STAR Provide more space for important parts – but don‘t lose context Methods:  Fisheye Views (Furnas:SIGCHI:1986)  Perspective Wall (Mackinlay:CHI:1991)  Document lens (Robertson:UIST:1993)  Etc.  Review and Taxonomy (Leung:TCHI:1994) F+C: Distortion-oriented

Robert Kosara, Helwig Hauser 8InfoVis STAR F+C: Magic Lenses Provide more/other information for objects on screen Several similar techniques Methods:  2D Taxonomy (Bier:CHI:1994)  3D (Viega:UIST:1996)  F+C Screen (Baudisch:UIST:2001)

Robert Kosara, Helwig Hauser 9InfoVis STAR F+C: In-Place Point the user at important objects – use different style, color, etc. for F+C Methods:  GeoSpace (Lokuge:CHI:1995)  Cheops (Beaudoin:Vis:1996)  Semantic Depth of Field (SDOF) (Kosara:InfoVis:2001)

Robert Kosara, Helwig Hauser 10InfoVis STAR Multiple Views Different views on the same data (Baldonado:AVI:2000, North:HCS:2000) Provide  More and  Different information  Interaction  Focus+Context

Robert Kosara, Helwig Hauser 11InfoVis STAR Linking&Brushing (L&B) Brush data values in one view See the same values highlighted in other view (linking) (Becker:Technometrics:1987) Different kinds of brushing (Wills:InfoVis:1996)

Robert Kosara, Helwig Hauser 12InfoVis STAR 1D Methods Essentially linear work with data of any dimensionality or structure Methods  Table Lens (Rao:CHI:1994)  + Multiple focal levels (Tenev:InfoVis:1997)  SuperTable + Scatterplot (Klein:IV:2002)  LensBar (Masui:InfoVis:1998)

Robert Kosara, Helwig Hauser 13InfoVis STAR 2D Methods Overlapping scalar fields and GIS Scalar fields  Map with bars (Healey:TVCG:1999)  Enridged contour maps (Wijk:Vis:2001)  Oriented texture slivers (Weigle:GI:2000) Geographical Information Systems (GIS)  GeoSpace (Lokuge:CHI:1995)  Macroscope (Lieberman:UIST:1994)  Etc.

Robert Kosara, Helwig Hauser 14InfoVis STAR High-Dimensional („nD“) Methods Data is  High-Dimensional  Unstructured Different Types of Methods  Glyphs  Non-Orthogonal display  Projections and selections  Interaction-rich methods

Robert Kosara, Helwig Hauser 15InfoVis STAR nD: Glyphs Encode data in the features of an object Methods  Chernoff faces (Chernoff:AmStat:1973)  Emphatic Visualization Algorithm (Loizides:IV:2002)  Cardiovascular data (Agutter:InfoVis:2001)  Shapes (Ebert:CG:2000)  Stick Figures (Pickett:SMC:1988)

Robert Kosara, Helwig Hauser 16InfoVis STAR nD: Non-Orthogonal Display Display dimensions non-orthogonally Methods:  Parallel coordinates (Inselberg:InfoVis:1999)  Angular Brushing (Hauser:InfoVis:2002)  Higher order PCs (Theisel:CGF:1998)  Star plot (Chambers:1983)  Circle Segments (Ankerst:Vis:1996)  Sunflower (Rose:InfoVis:1999)

Robert Kosara, Helwig Hauser 17InfoVis STAR nD: Projections and Selections Reduce the dimensionality by projection and selection Methods:  Scatterplot matrix (Cleveland:1985)  Hyperslice (Wijk:Vis:1993),Hypercell (Santos:VisSym:2002)  Dimensional stacking (LeBlanc:Vis:1990)  Prosection Views (Furnas:JCGS:1994), Prosection Matrix (Spence:InfoVis:1995)

Robert Kosara, Helwig Hauser 18InfoVis STAR nD: Interaction-rich Methods Interaction-intensive methods for nD Methods:  Worlds within worlds (Feiner:UIST:1990)  Reorderable Matrix (Bertin:1981, Siirtola:IV:1999)  Advizor (Eick:TVCG:2000)

Robert Kosara, Helwig Hauser 19InfoVis STAR Hierarchical (Tree) Data Very common in literature Special Case of graphs – but separate methods make sense Different Methods  Side View  Top View

Robert Kosara, Helwig Hauser 20InfoVis STAR Trees: Side View Show the branch structure of the tree Methods  Cone and cam trees (Robertson:CHI:1991)  Generalized cone trees (Jeong:InfoVis:1998)  Cylindrical trees (Dachselt:InfoVis:2001)  Pyramids (Andrews:IV:2002) AsbruView (Kosara:AIMJ:2001)  Botanical tree vis (Wijk:InfoVis:2001)

Robert Kosara, Helwig Hauser 21InfoVis STAR Trees: Top View Space-filling trees Methods  Treemap (Shneiderman:ToG:1992)  Squarified treemap (Bruls:VisSym:2000)  Ordered treemap layout (Shneiderman:InfoVis:2001)  Quantum/Bubble treemap (Bederson:UIST:2001)  Cushion treemap (Wijk:InfoVis:1999)

Robert Kosara, Helwig Hauser 22InfoVis STAR Network (Graph) Data Directed and undirected graphs, computer networks Methods:  Graph drawing survey (Herman:TVCG:2000)  H3 (Munzner:InfoVis:1997)  Circles (Yee:InfoVis:2001)  MBone (Munzner:InfoVis:1996)  SeeNet (Becker:TVCG:1996)

Robert Kosara, Helwig Hauser 23InfoVis STAR Temporal Data Record past and plan the future Past:  Spirals (Alexa:InfoVis:2001)  Cluster & calendar (Wijk:InfoVis:1999) Future:  SOPOs (Rit:AAAI:1986)  AsbruView (Kosara:AIMJ:2001)

Robert Kosara, Helwig Hauser 24InfoVis STAR Textual Data Why text is more than one-dimensional Methods:  SPIRE (Wise:InfoVis:1995)  ThemeRiver (Havre:TVCG:2002)  Shape-based (Rohrer:CGA:1999)  Galaxy of news (Rennison:UIST:1994)

Robert Kosara, Helwig Hauser 25InfoVis STAR Show structure of program, support software testing Methods:  Seesoft (Eick:TSE:1992, Ball:Computer:1996)  Program testing (Eagan:InfoVis:2001)  InfoBUG (Chuah:InfoVis:1997)  Program structure (Telea:VisSym:2002) Software Visualization

Robert Kosara, Helwig Hauser 26InfoVis STAR InfoVis and SciVis Support and enhance SciVis with InfoVis Examples:  WEAVE (Gresh:Vis:2000)  3D transfer functions (Kniss:Vis:2001)  Smooth brushing (Doleisch:WSCG:2002)

Robert Kosara, Helwig Hauser 27InfoVis STAR Perception, User Studies Find out how effective a method is Papers:  2D vs. 3D (Robertson:UIST:1998, Smallman:CGA:2001, Tavanti:InfoVis:2001, Cockburn:CHI:2002)  SDOF-Study (Kosara:VisSym:2002)  „Which Blair Project“ (Rogowitz:Vis:2001)  Reorderable matrix study (Siirtola:IV:1999)  Tree visus (Barlow:InfoVis:2001)

Robert Kosara, Helwig Hauser 28InfoVis STAR The Future of InfoVis Large Data  Fast  Visually effective More integration of different methods More interaction in methods More perception, cognition, studies InfoVis as secondary task