Metaphors to Spatialize Information

 

1. Issues, opportunities and challenges

 

2. by:

 

2. 1. Prof. Micha Pazner,

 

2.2. National Center for Geographic Information and Analysis

2.3. University of California Santa Barbara

2.4. and Department of Geography

2.5. University of Western Ontario, London, Canada

3. Hits as pits on an English language map

 

3.1. a map that simulates internet search results, depicting "hits" as impact craters

3.2. * HitsAsPits *

4 Islands in a sea of (non) knowledge

 

4.1. same idea, different metaphor

4.2. * WordIslands *

5. The objectives of this presentation are:

 

6. The main objective:

 

6.1. to make the case for professional and systematic use of the field of geographic information science (GISci) and its tools geographic information systems (GIS). 6.1.1. to guide the optimal use of spatial metaphors

 

6.1.2. for the spatial processing of information

 

7. A specific objective:

 

7.1. to introduce a cartographic coordinate system for language

 

7.1.1. along with the wordfield metaphor

 

8. The structure of the talk

 

8.1. The Linguistic Landscape Map and thewordfield metaphor

 

8.2. A few words on GIS, GlScience, and Spatialization

8.3. Wrap-up: issues, opportunities and challenges

 

9. The Linguistic Landscape Map and theword field metaphor

 

9.1. ... for the spatial represention and processing of large amounts of text

 

 

 

 

10. We would like to create an information space

 

10.1. into which concepts can be mapped

 

10.2. and spatial operations can then be performed to

 

10.2.1. query, model, and visualize relationships between different concepts

 

11. To this end we would like to create an information space that is compatible with a grid based GIS

 

11.1. the data model is an aligned stack of map layers

 

11.2. We would like to be able to put any word or concept in the language in its place on our map

 

12. The linguistic landscape map metaphor

 

12.1. we treat the language domain as a map space

 

12.1.1. initially an empty canvass, our landscape maps will eventually contain abundant information

 

13. we make use of Cartographic Language (McEachren 1994) to represent Language

 

13.1. linguistic objects are mapped as landscape elements

 

14. what's a good landscape element metaphor for a word?

 

14.1. let's try: word or concept asfield

 

14.1.1. (a semantic field represented by a mapped field)

 

15. imagine a rural landscape where a word is a green field

 

15.1. word as area that has a certain size, shape, perimeter, and internal structure and pattern
15.2.  Word as Field

 

16. next, we need a system of coordinates

 

17. How are we to visually represent many concepts next to one another?

 

17.1. How are we to lay out a word or concept space?

 

17.2. What will be the planar coordinates of such an information space?

 

17.2.1. i.e. what will the X and Y axis measure?

 

18. the Alphabetical Information Space Coordinate System
Alphabetical Coordinate System

 

18.1. a fixed relative coordinate system for mapping words

 

19. A word's X coordinate will depend on

 

19.1. what the first (Capital) letter is, the mix of letters in a word, and word length.

 

20. The X coordinate for Dog is 361 and for God it is 656.

 

20.1. Note that while they are the same length and have the same letter mix, even the relative displacement is not identical (off by 5).

 

21. A word's Y coordinate will also depend on

 

21.1. what letters are present and in what order, but using a totally different numerical scheme.

 

22. The Y coordinate for Dog is 844 and for God it is 547.

 

22.1. Note that while they are the same length and have the same letter mix the result is different, with Dog having the higher value this time.

 

23. While

 

23.1. X is a spatial numerical expression of word field size,
)

23.2. Y is an aspatial numerical expression of word letter pattern.

 

Word Map24. Words that are less similar in length and composition will have substantially different coordinate values

 

24.1. Concept is (y=1553 ,x--303)

 

24.1.1. i.e. "the highest leftmost pixel occupies a grid square whose address is (1553, 303)"

 

25. However Concept, Concert and Concern would have partial overlap in the current design.

 

25.1. This can be addressed in iterative refinements of the current addressing system.

 

25.2. Overlap is a permissible, common, and addressable situation in cartography.

 

26. What does the distance mean?

 

26.1. X axis is Alphabetical distance at the global level, with word size distance locally within a letter

 

26.1.1. note that short words leave space for longer words...

 

26.1.2. note that the either axis could be designated (i.e. Y could be the Alphabetical axis if there's a good reason...

 

26.2. Y axis is an arbitrary numerical 'value spreading' function

 

 

27. Advantages

 

27.1. consistent (fixed relative coordinate system)

 

27.2. dominated by Alphabetical order supported by one, and only one, axis

 

27.3. lends itself to layering

 

27.4. lends itself to spatial processing for analysis and visualization

 

27.5. economical (files are suitable for PC and network traffic)

 

28. Disadvantages

 

28.1. not ordered by categories

 

28.2. not ordered by meanig

 

28.3. not ordered by context (cf. multidimensional scaling)

 

28.4. overlap is allowed and must be dealt with using overlay methods

 

29. A few comments about the use of metaphors

 

30. Germane metaphors

 

30.1. weak (not necessarily inferior choices) metaphors versus strong (Couclelis)

 

30.1 .1. weak: (e.g. "desktop")

 

30.1.2. weak metaphors that can fade in and out so that we don't become captives of metaphors

 

30.2. strong (e.g. flight sim)

 

31. metaphor as design tool

 

31.1. a good metaphor guides the design of the map in useful directions

 

31.2. for spatial processing

 

32. a simple metaphor of a 'boring rural field' is a good place to start

 

32.1. simple areal feature (can be disjoint)

 

32.2. we are starting from solid ground...and can build more sophisticate~etaphors from the ground up

 

 

 

33. Summing up our metaphor

 

34. A cartographic stem-and-leaf plot for text:

 

34.1. What the graphic stem-and-leaf plot (Tukey) is to numbers,

 

34.2. the word-as-field map is to text

 

35. Text built text coordinates

 

35.1. or concept built concept coordinates

 

35.2. ie. like data built data measures

 

36. some attributes are encoded in the X and Y value

 

36.1. used to create the space (see assumptions below)

 

37. multifunctioning graphic elements (Tufte)

 

37.1. the word is explicitly labeled

 

37.1.1. it is not just a blob- it is readable

 

38. the shape size and other graphic elements are used as patterns

 

38.1. by humans

 

38.2. and can be used by the machine

 

39. What we have here are words and concepts as areal entities

 

39.1. These are literally 'semantic fields'

 

39.2. That are built hierarchically out of pixels

 

39.2.1. which form letter areas

 

39.2.1.1. which jointly form the area for a word or concept

 

40. The Semantic Field metaphor

 

40.1. Words (text) are used to represent concepts

 

40.2. However, the words are additionally treated as (graphic) areal entities (duality)

 

41. The metaphor:

 

41.1. A word expressing a given concept is viewed as an areal spatial object a field of letters.

 

42. Assumptions

 

42.1. we have fi concepts (in the form of words)

 

42.2. each concept can be mapped to a cartographic location on the information map

 

42.3. concepts have i attributes (or properties)

 

42.4. attribute x and attribute y are used to fix the location of the concept in the space

 

43. attribute z is represented by the numeric value of the pixels that makes up the concept

 

43.1. attributes Zi (i = 1 to m) are represented using a separate layer for each attribute,

 

43.2. if for example, the attribute is "3178" for the number of times the word 'concept' was encountered in an Internet search engine query, then the pixels of 'concept' would be coded as 3178.

 

43.3. note that the z value can represent qualitative nominal values as well as quantitative values.

 

44. A few words on GIS, GiScience, and Spatialization

 

45. What essentially are GIS?

 

45.1. Geographic Information Systems can be represented by a Venn Diagram that has Automated Cartography, Spatial Analysis, and Geographic Database circles.

 

46. What is all the excitement surrounding GIS about?

 

46.1 a new spatial literacy

 

46.1.1. we can not only think spatially (internal representation)

 

46.1.2. but actually do a lot more about it (external representation)

 

47. from descriptive to derivative: the ability to progressively generate new information

 

47.1. --- and the ability to make implicit spatial relations explicit

 

48. Examples of GISci models that are available

 

48.1. the cellular exploratory spatial analysis (CESA) subset
48.1.1. * SIP models *

SIP models

48.2. *SIP tasks*
SIP tasks
 

49. GIS and Geography are strongly intertwined

 

49.1. something big is happening to Geography...AAG specialty membership as an indicator

 

49.2. Allied technical fields create an even more massive army:

 

49.2.1. e.g.: cartography, remote sensing, GPS, math/stats modeling, etc.

 

49.3. Three Geography GIS textbooks have appeared in January 1997

 

50. Fundamentals of Geographic Information Systems, Michael N. DeMers, John Wiley & Sons, 1997.

 

50.l.· "This is a book about geography. It is also about Geographic Information Systems

 

(GIS)?" (p.3)

 

· The book emphasizes spatial concepts and ideas over tools.

 

· Fundamentals ... is aptly titled-the book does an admirable job at laying down in an orderly

 

fashion the conceptual foundations of a new discipline.

 

50.3.1. (Pazner 1997, book review to appear in Transactions in GIS, Vol.1 No.3)

 

51. Spatialization - An important emerging field

 

51.1. · Spatialization entails the modern use of geographic metaphors and spatial and graphic processing for representing non-spatial information.

 

51.2. · A conceptually and methodologically challenging fast-growing research field,

 

51.2.1. - the main problem seems to be how to create the new space

 

52. A quote:

 

52.1. "Will there be a Netscape of Virtual Cartography? Or are Netscape, Microsoft, Oracle and every other company creating virtual environments on the Internet already in the cartography business? Schrage will explore the ways technology, complexity, and cartographic expertise may combine to create new marketplaces for maps"

 

52.1.1. Michael Schrage (MIT), Keynote Speaker on "Multimedia, Hypermaps, and Cartopreneurs:

 

Mapping the Future of the Marketplace", GIS LIS '96, November, Denver, CO.

 

53. A growing number of innovative software products are being developed in this area

 

53.1. Microsoft has hired over 150 people to work in cartography.. 54. Wrap-up: issues, opportunities and challenges

 

55. General main message: It makes a lot of sense to represent information using spatial metaphors.

 

55.1. The reason being that substantial benefits can be reaped by applying Geographic Information Science and modern spatial analysis, modeling and visualization.

 

56. Spatialized information shouldn't be seen just as a candidate for visualization

 

56.1. but also as a candidate for further processing to 'tease out' derivative and implicit relationships.

 

57. GISci offers the opportunity to do coupled spatial database querying, analysis, and visualization.

 

58. Specific main message: to present "woordinates" and word fields.

 

59. An experimental information space was created that is compatible with a grid based GIS

 

59.1. Features in this space can benefit from the quantitative and visual functionality of~ spatial processing.

 

60. "How can we...." questions?

 

60.1. We have a mechanism for coming up with solutions

 

60.2. To get to the answer think of it in terms of cartography and GISci and spatial image processing. There is a body of accumulated expertise there.

 

60.2.1. for example: How do we deal with scale and how can we apply cartographic generalization?

 

60.2.1.1. Answer: In a similar way that fields can be rescaled and generalized in maps and images. Period.

 

61 We should think in terms of building multi-disciplinary teams that include GISci specialists, cartographers and geographers.

 

61.1. and not just linguists, computer scientists, statisticians, psychologists, etc.

 

62. There is a clear need to develop integrated applications:

 

62.1. information system (DBMS. query, search, processing)

 

62.2. geographic information system (e.g. ESRI ArcInfo and ArcJView)

 

62.3. adapted virtual reality user interface (e.g. MS W95 flight simulator)

 

62.4. data conversion software between each stage

 

63. GISci challenges:

 

64. Creating operational linguistic spatial databases

 

64.1. E.g. of a whole Dictionary or Thesaurus

 

65. Using linguistic spatial database functions and models

 

65.1. Examples of GISci models that are available

 

65.1.1. the cellular exploratory spatial analysis (CESA) subset

 

65.1.1.1. *SIPmodels*
65.2. *SIPtasks*

 

66. Generating output products

 

66.1. independent

 

66.2. to be used as input to the next stage

 

67. The End