Schuurman: GIS: A Short Introduction: Ch. 1

Schuurman Ch 1: Introducing the Identities of GIS

I. The Success of GIS

Boom in GIS: is it now what Geography is? Ubiquitous technology
• technological advances, widespread adoption
• people may not have heard of GIS but they use it and are affected by it
WWW) GoogleMaps or Yahoo Maps or MapQuest are all GIS
WWW) municipal, utilities management: DALIS project
WWW) business and marketing: PRIZM data: you are where you live

• “This book is designed to inform the reader about precisely how GIS affects them as well as myriad social processes” (1)
• a more human & social approach to technology, intellectual rather than tech.

The problem of GIS and geography: love/hate
• one lense or way of understanding but dominating
• quantitative vs. qualitative methods
• epistemology: The branch of philosophy that studies the nature of knowledge, its presuppositions and foundations, and its extent and validity. How we know.

Identity of GIS: what is it?

WWW) Del Co. GIS: a tool for storing complex data; practical problem solving
• where

PROP) Student Project: character of “neighborhoods” in Delaware: mental maps
• how to collect qualitative data and map it

What is most important when locating a recreational trail?

• logic of quantitative methods for optimizing, or qualitative data used to
anticipate how people will react (and why)? Epistemological issues!

II. Where Does GIS Come From?
1960s: technology and epistemology

WWW) McHarg and the overlay method: locating a road: done manually
• encode in a computer: technology and a particular way of knowing
• what is not taken into account in this approach
• spatial analysis: a means of extracting information (knowledge) from data
• let a computer do what McHarg did
• maps allow us to see raw data, or interact with data as we are analyzing
it, or show the results of what we did

1950s-60s: development of computational analysis and spatial analysis tools
• wed technology to methods of knowing
WWW) Harvard: spurred development of ESRI

III. The Messy Business of Digging for Roots: GIS’s Intellectual Antecedents

Examples of the precursors of GIS: technology is easy, epistemology not
ex) point, line, area: 1930s for map symbolization; basis of “vector data”
ex) certain kinds of data easier to collect and analyze and map, they seem more intuitive maybe because they are what we are used to doing.
ex) non-visual vs visual analysis (visualization)

IV. What does GIS stand for?

Definitions describe technology (systems; application): GISys
• hard/software for data input, analysis, output
• black box: assume the methods in the software are legitimate, don’t question

Definitions describing methods and process (science; theory): GISci
• origin of the methods, critique of the methods, new methods
• conceptual models of geographic space, sphericity of the real world vs. flat world of GIS, uncertainty and error, analytical methodologies, cognitive aspects.

• also Participatory GIS, Critical GIS: myriad of human/social issues
• justifying and shaping an intellectual/academic role in GIS
• myriad of issues of intellectual importance (that one may not think about at all if only approaching GIS as black box technology).

Epistemology (how we know) and ontology (what the world must be like in order to be known): evolution/science vs creationism/intelligent design
• does geography (and its concepts/theories) drive GIS, or does GIS drive
geography? Debates in the field.

V. Data in, Information Out: Common Ground between GISys and GISci

GISys and GISci hard to differentiate in practice

ex) data classification: the categories we put things into
ex) house: what defines what a house is? Is an apartment a house? A
dorm? A condo? A long-term residential hotel?

• the kind of issue both Sys and Sci people have to deal with

ex) boundaries: complexity in drawing: neighborhood boundaries have to
be drawn if you are using GIS, but where to draw them? How do
you define a neighborhood (which is a classification of place)

Visualization: using intuition and knowledge to see patterns and connections: different epistemological approach

ex) Hepatitus A in daycares p. 14
WWW) Snow example: Broad St. pump and cholera p. 15

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