Metaphors to Spatialize
1. Issues, opportunities and challenges
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
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
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
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
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
17.2.1. i.e. what will the X and Y axis measure?
18. the Alphabetical Information Space 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
23.1. X is a spatial numerical expression of word field size,
23.2. Y is an aspatial numerical expression of word letter
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
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'
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
27.5. economical (files are suitable for PC and network
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
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
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
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
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
188.8.131.52. which jointly form the area for a word or
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.
42.1. 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
47. from descriptive to derivative: the ability to progressively
generate new information
47.1. --- and the ability to make implicit spatial relations
48. Examples of GISci models that are available
48.1. the cellular exploratory spatial analysis (CESA)
48.1.1. * SIP models *
48.2. *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
49.2.1. e.g.: cartography, remote sensing, GPS, math/stats
49.3. Three Geography GIS textbooks have appeared in January
50. Fundamentals of Geographic Information Systems, Michael
N. DeMers, John Wiley & Sons, 1997.
is a book about geography. It is also about Geographic Information Systems
· 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,
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
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
60.2.1. for example: How do we deal with scale and how
can we apply cartographic generalization?
184.108.40.206. 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,
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
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
65.1. Examples of GISci models that are available
65.1.1. the cellular exploratory spatial analysis (CESA)
66. Generating output products
66.2. to be used as input to the next stage
67. The End