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Representation

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Information Visualization
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Abstract

Illustrates some of the many ways in which data can usefully be transformed into images that are more easily understood. Attention is paid to limitations imposed by the human visual processing system, and to the considerable benefits that can be achieved by interaction.

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Notes

  1. 1.

    The second half of this report contains food recipes of the day. However, it is strongly recommended that grim details of the Crimean hospitals should not be perused before eating Nightingale’s – or indeed anyone else’s – recipes!.

  2. 2.

    As defined by Bertin (1967, 1983, p 73), ‘value’ is not restricted to a grey scale. As Bertin remarks, “One can pass from black to white by greys, by blues or by reds …’

  3. 3.

    Only the 25 %, 50 % (median) and 75 % quartiles are shown. Whiskers are omitted to reduce visual clutter.

  4. 4.

    A comment taken from Matthew Ericson’s keynote address at IEEE InfoVis 2007.

  5. 5.

    The 13 attributes are: Model; Release date; Max resolution; Low resolution; Effective pixels; Zoom wide (W); Zoom tele (T); Normal focus range; Macro focus range; Storage included; Weight (inc. batteries); Dimensions; Price.

  6. 6.

    The beneficial effect of animated transitions is revisited in Sect. 3.6.

  7. 7.

    Many representations of relational data require prior, and sometimes extensive, computation. This important topic is extensive and is not the subject of this book.

  8. 8.

    relation (n): a logical or natural association between two or more things; relevance of one to another; connection.

  9. 9.

    If, as discussed in Sect. 3.5, the typical reader of the New York Times feels challenged by scatter plots, it would be of interest to know their reaction to, and understanding of, Venn diagrams.

  10. 10.

    Note the designated root node: you can pick up a tree by any other node and it still has the properties of a tree.

  11. 11.

    The Sunburst display is often classed as a ‘Space-filling technique’ in view of its tendency to make maximal use of display space, though the Tree Map can occupy a full rectangular display.

  12. 12.

    See the discussion of ‘Focus+Context’ in Chap. 4.

  13. 13.

    The encoding of vital human signs such as blood pressure in sound was found to be supportive of an anaesthetist’s task during long operations (Watson et al 1999; Watson and Sanderson 2004). An example of olfactory encoding is provided by the practice adopted by drivers of express steam locomotives of embedding aniseed balls within those parts of the engine that might get overheated and, in so doing, release the smell of anis that could be detected in the driver’s cab.

References

  • Ahlberg C, Shneiderman B (1994) Visual information seeking: tight coupling of dynamic query filters with starfield displays. In: ACM, proceedings CHI’94, pp 313–317

    Google Scholar 

  • Ahlberg C, Williamson C, Shneiderman B (1992) Dynamic queries for information exploration: an implementation and evaluation. In: ACM, Proceedings CHI’92, pp 619–626

    Google Scholar 

  • Aigner W, Miksch S, Schumann H, Tominski T (2011) Visualization of time-oriented data. Springer, London

    Book  Google Scholar 

  • Andrews K, Heidegger H (1998) Information slices: visualising and exploring large hierarchies using cascading, semicircular discs. In: IEEE, symposium on information visualization (InfoVis ’98) Late breaking paper, 4 pp

    Google Scholar 

  • Arnold CJ (1997) An archaeology of the early Anglo-Saxon kingdoms. Routledge, London

    Google Scholar 

  • Bertin J (1967) Semiologie graphique. Editions Gauthier-Villars, Paris

    Google Scholar 

  • Bertin J (1981) Graphics and graphic information-processing, Berlin, Walter de Gruyter: a translation of La Graphique et le Traitement Graphique de l’Information. Paris, Flammarion (1977)

    Google Scholar 

  • Bertin J (1983) Semiology of graphics (trans: Berg WJ). University of Wisconsin Press

    Google Scholar 

  • Biederman I (1987) Recognition-by-components: a theory of human image understanding. Psychol Rev 94(2):115–117

    Article  Google Scholar 

  • Buxton B (2007) Sketching user experiences. Morgan Kaufmann, Amsterdam

    Google Scholar 

  • Chernoff H (1973) The use of faces to represent points in k-dimensional space graphically. J Am Stat Assoc 68:361–368

    Article  Google Scholar 

  • Cleveland WS, McGill R (1984) Graphical perception: theory, experimentation and application to the development of graphical methods. J Am Stat Assoc 79(387):531–554

    Article  MathSciNet  Google Scholar 

  • Coekin JA (1969) A versatile presentation of parameters for rapid recognition of total state. In: IEE, proceedings of international symposium on man-machine interaction, Cambridge, England

    Google Scholar 

  • Davidson C (1993) What your database hides away. New Scientist, 9 January 1993, pp 28–31

    Google Scholar 

  • Dawson RJ McG (1995) The “unusual episode” data revisited. J Stat Educ 3:3, online

    Google Scholar 

  • Elmqvist N, Dragicevic P, Fekete J-D (2008) Rolling the dice: multidimensional visual exploration using scatterplot matrix navigation. IEEE Trans Vis Comput Graph 14:1141–1148

    Google Scholar 

  • Freeman LC (2005) Graphical techniques for exploring social network data. In: Carrington PJ, Scott J, Wasserman S (eds) Models and methods in social network analysis. Cambridge University Press, Cambridge, pp 248–269

    Chapter  Google Scholar 

  • Friendly M (1992) Mosaic displays for loglinear models, in ASA. In: Proceedings of the statistical graphics section, pp 61–68

    Google Scholar 

  • Friendly M (1994) Mosaic displays for multi-way contingency tables. J Am Stat Assoc (Theory Methods) 89(425):190–200

    Article  Google Scholar 

  • Friendly M (2000) Visualizing categorical data. SAS Institute Inc., Cary

    Google Scholar 

  • Garland K (1994) Mr. Beck’s underground map. Capital Transport Publishing, Harrow Weald

    Google Scholar 

  • Havre S, Hetzler B, Nowell L (2000) Visualizing theme changes over time. In: IEEE, proceedings symposium of information visualization, pp 115–123

    Google Scholar 

  • i2 (2006) www.i2.com

  • Inselberg A (1985) The plane with parallel coordinates. Vis Comput 1(4):69–91

    Article  MATH  Google Scholar 

  • Inselberg A, Dimsdale B (1990) Parallel coordinates: a tool for visualizing multidimensional geometry. In: IEEE, proceedings conference on visualization, pp 361–378

    Google Scholar 

  • Irani P, Tingley M, Ware C (2001) Using perceptual syntax to enhance semantic content in diagrams. In: IEEE, computer graphics and applications, September, pp 76–84

    Google Scholar 

  • Johnson B, Shneiderman B (1991) Tree-maps: a space-filling approach to the visualization of hierarchical information structures. In: IEEE, proceedings information visualization’91, pp 284–291

    Google Scholar 

  • Krzywinski M, Schein M, Birol I, Connors J, Gascoyne R, Horsman D, Jones SJ, Marra M (2009) Circos: an information aesthetic for comparative genomics. Genome Res 19:1639–1645

    Article  Google Scholar 

  • Lamping J, Rao R (1994) Laying out and visualising large trees using a hyperbolic space. In: ACM, proceedings UIST’94, pp 13–14

    Google Scholar 

  • Lamping J, Rao R (1996) The hyperbolic browser: a focus+context technique for visualising large hierarchies. J Vis Lang Comput 7(1):33–55

    Article  Google Scholar 

  • Lamping J, Rao R, Pirolli P (1995) A focus+context technique based on hyperbolic geometry for visualizing large hierarchies. In: ACM, proceedings CHI’95, pp 401–408

    Google Scholar 

  • Li Q, North C (2003) Empirical comparison of dynamic query sliders and brushing histograms. In: IEEE, proceedings symposium information visualization, pp 147–154

    Google Scholar 

  • Nightingale F (1858) Notes on matters affecting the health, efficiency and hospital administration of the British army. Harrison & Sons, London

    Google Scholar 

  • Ovenden M (2003) Metro maps of the world. Capital Transport Publishing, Harrow

    Google Scholar 

  • Rensink RA (2002) Change detection. Annu Rev Psychol 53:245–277

    Article  Google Scholar 

  • Robertson GG, Mackinlay JD, Card SK (1991) Cone trees: animated 3D visualizations of hierarchical information. In: ACM, proceedings CHI’91, pp 189–194

    Google Scholar 

  • Siirtola H (2000) Direct manipulation of parallel coordinates. In: Proceedings of the international conference on information visualization (IV2000), pp 373–378

    Google Scholar 

  • Siirtola H, Raiha K-J (2006) Interacting with parallel coordinates. Interact Comput 18(6):1278–1309

    Article  Google Scholar 

  • Simon H (1996) The sciences of the artificial, 3rd edn. MIT Press, Cambridge, MA

    Google Scholar 

  • Smith D (1999) The state of the world atlas, 6th edn. Penguin, London

    Google Scholar 

  • Spence R, Parr M (1991) Cognitive assessment of alternatives. Interact Comput 3(3):270–282

    Article  Google Scholar 

  • Spence R, Tweedie L (1998) The attribute explorer: information synthesis via exploration. Interact Comput 11:137–146

    Article  Google Scholar 

  • Stasko J, Zhang E (2000) Focus+context display and navigation techniques for enhancing radial, space-filling hierarchy visualizations. In: IEEE, proceedings symposium on information visualization, pp 57–65

    Google Scholar 

  • Stuckenschmidt H, v Harmelen F, de Waard A, Scerri T, Bhogal R, van Buel J, Crowsmith I, Fluit C, Kampman A, Broekstra J, van Mulligen E (2004) Exploring large document repositories with RDF technology: the DOPE project. In: IEEE, intelligent systems, pp 22

    Google Scholar 

  • Teoh ST, Ma K-L (2005) Hifocon: object and dimensional coherence and correlation in multidimensional visualization. In: Proceedings international symposium on visual computing (ISVC’05), pp 235–242

    Google Scholar 

  • Tweedie L, Spence R, Williams DML, Bhogal R (1994) The attribute explorer. In: ACM conference companion proceedings, CHI’94, pp 435–436. Also video proceedings

    Google Scholar 

  • Ware C (2012) Information visualization: perception for design, 3rd edn. Morgan Kaufmann, Amsterdam

    Google Scholar 

  • Watson M, Sanderson P (2004) Sonification helps eyes-free respiratory monitoring and task time-sharing. Hum Factors 46(3):497–517

    Article  Google Scholar 

  • Watson M, Russell WJ, Sanderson P (1999) Ecological interface design for anaesthesia monitoring. In: IEEE, proceedings OzCHI’99, pp 78–84

    Google Scholar 

  • Wattenberg M (2001) The shape of song, at http://www.bewitched.com/song.html Accessed 25 Dec 2013

  • Wattenberg M (2002) Arc diagrams: visualizing structure in strings. In: IEEE, proceedings symposium on information visualization, pp 110–116

    Google Scholar 

  • Wattenburg M (1999) Visualizing the stock market. In: ACM, proceedings CHI’99, pp 188–189

    Google Scholar 

  • Westphal C, Blaxton T (1998) Data mining solutions: methods and tools for solving real-world problems. Wiley, New York

    Google Scholar 

  • Williamson C, Shneiderman B (1992) The dynamic housefinder: evaluating dynamic queries in a real estate information exploration system. In: ACM, proceedings SIGIR’92, pp 339–346

    Google Scholar 

  • Wittenburg K, Lanning T, Heinrichs M, Stanton M (2001) Parallel bargrams for consumer-based information exploration and choice. In: ACM, proceedings UIST’01, pp 51–60

    Google Scholar 

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Exercises

Exercises

3.1.1 Exercise 3.1

Five students have taken exams in eight subjects and for each subject a maximum mark of ten has been assigned. Make a list of the questions that might be asked of this data by (a) a parent (b) a student (c) a subject teacher and (d) the head teacher. Aim for a total of at least ten questions. Write the questions on Post-Its and stick them on a wall, together with those of your colleagues, for reference during Exercise 3.2.

3.1.2 Exercise 3.2

The exam performance of the five students mentioned in Exercise 3.1 is shown below

Student

A

B

C

D

E

Subject

Art

10

1

5

3

2

Science

1

10

5

4

9

History

8

5

7

1

1

Sport

2

9

5

10

4

Physics

1

2

3

1

English

2

8

6

8

5

Chemistry

4

1

1

1

4

Mathematics

10

1

5

4

2

Without using a computer in any way, design and sketch one static representation of this data: no interaction with the representation is to be considered. Then see if it answers any of the questions generated in Exercise 3.1. Decide whether your representation exhibits object visibility or attribute visibility.

3.1.3 Exercise 3.3

See if you can effectively modify the representation you designed for Exercise 3.2 to indicate whether each exam result was an improvement on the score achieved the previous year.

3.1.4 Exercise 3.4

Figure 3.89 shows a student’s suggested representation of the data shown in Exercise 3.2. Critique this design, commenting on its advantages and disadvantages, and decide how the representation might usefully be modified. Incorporate these modifications in your own redesign.

Fig. 3.89
figure 89

Sketched representation of the data of Exercise 3.2 (Courtesy Max A.C. Poynton)

3.1.5 Exercise 3.5

Compose a mosaic plot representation of the Titanic data (Table 3.1) but using a different sequence of steps (for example survival – > gender – > class – > adult/child). List the observations that can readily be made by looking at the result. Are they different from those triggered by the representations derived from Fig. 3.15?

3.1.6 Exercise 3.6

The London Underground transportation map contains no distance or journey time encoding. With sketches, show how this data can be represented. Would it be useful?

3.1.7 Exercise 3.7

For your school or university or department (real or imaginary) design a representation of scholastic achievements (e.g., marks in 12 subjects in each of 5 year groups) that will show not only the general level obtained but also (1) the way in which achievement levels are changing, (2) the proportion of students obtaining better than a pass mark, and (3) the number of students taking a particular subject. Design the representation so that it can be printed on a card that slides easily into the pocket (e.g., one-third of A4).

3.1.8 Exercise 3.8

Sketch possible static representations of human relationships, both formal (e.g., marriage, births, deaths, divorce) and informal (e.g., co-habiting), test them on real examples and identify the advantages and disadvantages of each.

3.1.9 Exercise 3.9

Bus, metro and train routes are typically represented by annotated lines between nodes. However, in some large cities (London, for example) there are so many routes that a journey may well involve intermediate changes and be very difficult to plan. Explore the potential of adding, to the node-link route representation, some overall directional indicators that give a ‘first glance’ suggestion as to which route might be best for a given journey.

3.1.10 Exercise 3.10

Select one of the folders on your laptop which contains at least two levels of hierarchy and draw a treemap representation of its contents.

3.1.11 Exercise 3.11

Repeat Exercise 3.10 and sketch a hyperbolic browser representation.

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Spence, R. (2014). Representation. In: Information Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-07341-5_3

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  • DOI: https://doi.org/10.1007/978-3-319-07341-5_3

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