Cognitive models of visual sensemaking

Cognitive Models of Visual Sensemaking Ed H. Chi

innovation & knowledge creation l foraging for information l making sense of it l “crystallizing” it into new knowledge l sharing it with others 2 Ed H. Chi - Visual Sensemkaing 12-09-1999

scientific knowledge grows exponentially Journals 1000000 100000 10000 1000 Divided by 100 earth’s 10 population 1 1750 1800 1850 1900 1950 2000 0.1 0.01 Journals increase 10X every 50 years 3 Ed H. Chi - Visual Sensemkaing 12-09-1999

human capacity 1000000 100000 10000 1000 100 10 1 1750 1800 1850 1900 1950 2000 0.1 0.01 Year 4 Ed H. Chi - Visual Sensemkaing 12-09-1999

visions of the future: it gets worse l Future = more information l Future = greater change 5 Ed H. Chi - Visual Sensemkaing 12-09-1999

The Real Problem “What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.” ~Herb Simon (Nobel Prize Winner) as quoted by Hal Varian Scientific American 9/1995 6 Ed H. Chi - Visual Sensemkaing 12-09-1999

a user interface goal H ZOHGJ NQR H FUHDV LQ knowledge acquired or created maximize cost of interaction GHFUH DVH F R VWV 7 Ed H. Chi - Visual Sensemkaing 12-09-1999

Cost of Knowledge Characteristic Function Gain in Knowledge Cost [Time] 8 Ed H. Chi - Visual Sensemkaing 12-09-1999

Visualization Toolbox Doctrine Idea expressed by: l “A graphic is never an end in itself; it is a moment in the process of decision- making.” Jacques Bertin, 1977 Graphic Information Processing 9 Ed H. Chi - Visual Sensemkaing 12-09-1999

Visual Sensemaking Cycle LWHUDWH 9rsvvtÃurÃiyr DrrÃhqÃqrpvqr 9rsvvtÃurÃqhh DrhpÃvuÃvr 8uvtÃhÃhhyvphyÃ UhpvirÃurÃhyr hihpv vÃvr 8uvtÃvhyvhvÃ 6qvtÃhÃprvtÃ hihpv yhthtr 10 Ed H. Chi - Visual Sensemkaing 12-09-1999

Information Level l Goal of sensemaking is to discover new higher-level knowledge in the information – Elementary or Local Level: Uncovering local info in raw data, i.e. detail-on-demand. – Intermediate or Comparison Level: Relationships between subsets of info. – Overall or Global Level: Condensed knowledge from the correlation between one aspect of the data with another aspect. 11 Ed H. Chi - Visual Sensemkaing 12-09-1999

Data State Reference Model l Uses four data DATA DATA STAGE OPERATOR representation DATA TRANSFORMATION stages ANALYTICAL ANALYTICAL l Operators between STAGE REPRESENTATION OPERATOR and within stages VISUALIZATION TRANSFORMATION l State Model VISUALIZATION VISUALIZATION STAGE REPRESENTATION OPERATOR VISUAL MAPPING TRANSFORMATION VIEW STAGE VIEW OPERATOR 12 Ed H. Chi - Visual Sensemkaing 12-09-1999

DATA DATA STAGE State Stages OPERATOR DATA TRANSFORMATION – Value (Data) l unprocessed abstract data not ANALYTICAL ANALYTICAL STAGE ready for direct viewing. REPRESENTATION OPERATOR – Analytical Abstraction l partially processed data not VISUALIZATION TRANSFORMATION ready for mapping. – Visualization Abstraction VISUALIZATION VISUALIZATION STAGE l processed data ready for REPRESENTATION OPERATOR mapping. VISUAL MAPPING – View TRANSFORMATION l data mapped into graphical representation for display. VIEW STAGE VIEW OPERATOR 13 Ed H. Chi - Visual Sensemkaing 12-09-1999

Transformation Operators (between stage) DATA DATAA STAGE OPERATOR DATA – Data Transformation TRANSFORMATION l i.e. extract web page ANALYTICAL ANALYTICAL linkage to create STAGE REPRESENTATION OPERATOR graph – Visualization VISUALIZATION TRANSFORMATION Transformation l i.e. breadth first VISUALIZATION VISUALIZATION STAGE traversal to create tree REPRESENTATION OPERATOR – Visual Mapping VISUAL MAPPING Transformation TRANSFORMATION l i.e. Disk Tree VIEW STAGE VIEW OPERATOR 14 Ed H. Chi - Visual Sensemkaing 12-09-1999

Within Stage Operators DATA DATA STAGE – Data Stage Operator OPERATOR l i.e. filtering based on keyword DATA TRANSFORMATION – Analytical Abstraction Stage ANALYTICAL Operator ANALYTICAL STAGE REPRESENTATION OPERATOR l i.e. filter, normalize vector – Visualization Abstraction VISUALIZATION TRANSFORMATION Stage Operator l i.e. filter, variable-to-axis VISUALIZATION VISUALIZATION STAGE REPRESENTATION OPERATOR mapping – View Stage Operator VISUAL MAPPING TRANSFORMATION l i.e. filter, rotate, scale, translate VIEW STAGE VIEW OPERATOR 15 Ed H. Chi - Visual Sensemkaing 12-09-1999

random number value- generator Data filtering State Model seed Data create random Transformation 3D point set l Many views and Analytical 3D point Representation values set – node = data state Visualization Voronoi Delaunay Transformation – edge = transform Diagram Triangulation data from one state Visualization Tetrahedra to another state Representation collection Edge Transparent Edge Render render Render Visual Mapping Transformation visualization View focus rotate 16 Ed H. Chi - Visual Sensemkaing 12-09-1999

Example Sensemaking of Evolving www.xerox.com

Web Analysis Operators Type operator Description Within Value Filter-Value Create a subset of the data. For example, create a subset of data containing only files that are reachable within four clicks of the root node. Data Extract linkage Create linkage graph from the hypertext files. Transformation information Extract usage Produce daily summarization of each file’s access frequency and the usage information flow from one file to another (hop count). Within Analytical Cluster nodes Produce classes of the items, as well as identify groups of users, using Abstraction several different clustering algorithms. Visualization Breadth First Traversal Generate a hierarchy that can be visualized using various tree visualization Transformation techniques. Since the Xerox web site is highly hierarchical in nature, this generates a useful view of the entire site. Within Usage Frequency Generates a frequency pattern over the web site, which can then be Visualization Pattern Algebra subtracted/added/averaged with other patterns from other weeks. Abstraction Spreading Activation Compare/aggregate Spreading Activation patterns by subtracting/ adding Pattern Algebra one with another. Visual Mapping Display Disk Tree Layout hierarchy based on a planar circle. This is our primary Transformation visualization technique used to visualize large hierarchies. Because it is a 2D technique, we can embed additional attributes using glyphs on the third dimension. Display Cone Tree Layout hierarchy based on a 3D cone. A 3D hierarchy visualization technique that shows the various levels in the tree extremely well. Apply Coloring Pattern Map color onto a displayed tree based on numeric item attributes. 18 Ed H. Chi - Visual Sensemkaing 12-09-1999 Display Pattern Glyph Show the Spreading Activation pattern on top of the Disk Tree using

Filter web page Value Value collection First Cycle Data create Transformation web page linkdage l Data: the whole Analytical graph Abstraction xerox.com web site breadth Visualization depth first first Transformation traversal traversal l Map to Cone Trees l Usage map to hierarchy Visualization Abstraction color Disk Cone Tree Disk Tree Visual Mapping Tree Transformation visualization View focus rotate 19 Ed H. Chi - Visual Sensemkaing 12-09-1999

First Sensemaking Cycle Time Color scale 20 Ed H. Chi - Visual Sensemkaing 12-09-1999

Filter web page Value Value collection Second Cycle Data create Transformation web page linkdage l Changing Analytical graph Abstraction representation to Disk Tree breadth Visualization depth first first Transformation traversal traversal hierarchy Visualization Abstraction Disk Cone Tree Disk Tree Visual Mapping Tree Transformation visualization View focus rotate 21 Ed H. Chi - Visual Sensemkaing 12-09-1999

2nd Sensemaking Cycle 22 Ed H. Chi - Visual Sensemkaing 12-09-1999

Usage Filter web page Logs Value Value collection 3rd Cycle Extract Data create Usage Transformation web page Pattern linkdage l Usage Substract Analytical graph Pattern Abstraction Pattern Substraction breadth Visualization first Transformation Associate traversal with Doc pairs hierarchy Visualization Abstraction Disk Tree Cone Disk Tree Visual Mapping Tree Transformation visualization View focus rotate 23 Ed H. Chi - Visual Sensemkaing 12-09-1999

Summary l a cognitive model for visualization called visual sensemaking cycle – define problem and operators – use operators to make sense of an aspect of the data – iterate 24 Ed H. Chi - Visual Sensemkaing 12-09-1999

advantages of information visualization l increased resources l high bandwidth interaction via the human gaze system l parallel perceptual processing l offload cognitive work to perceptual system l expand working memory 25 Ed H. Chi - Visual Sensemkaing 12-09-1999

advantages of information visualization l reduced search l localityof processing l high data density l spatially indexed addressing l recognition instead of recall l abstraction and aggregation l enhanced recognition patterns l perceptual inferences of values, relations, trends, etc. 26 Ed H. Chi - Visual Sensemkaing 12-09-1999

Cognitive models of visual sensemaking

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