Decomposing the Infinitely Complex World

It is useful at the outset of this section to stop reading for a moment. If you are inside, find a window and look out at the world you can see from your vantage point. Or, better yet, take a break and head out for a short walk to look at the world around you. If you do not want to go for a short walk, perhaps visualize your surroundings outside. What do you see? If you’re in a city, you might see buildings of various heights. Roads. Streetlamps. Cars. Perhaps you’re surrounded by hills, lakes, mountains, trees. How does one translate this infinitely complex world into data that can be arranged, rearranged, manipulated, and analyzed? Our “data” in a GIS is the simplified, abstracted version of all these things (and more). As a well-known introductory text to GIS puts it,

Our complex, dynamic, multidimensional, multiscaled world contains infinite and unmanageable sets of phenomena. To bring some coherence to these phenomena, we need to abstract the objects of interest and define them in terms of their attributes (properties), geographical location (spatial coordinates or geometry), and relationships (topology, hierarchy, etc.). (Burrough, McDonnel & Lloyd, 2015, p. 22)

This is not a simple process. Decisions must be made to highlight specific aspects of a feature, often at the expense of others.

Scale

“Scale” in GIS is more than just “zooming in” or “zooming out.” The concept is fundamental to how we interpret and represent phenomena. It is a deceptively simple term. With the democratization of mapping tools and technologies it has become a famously slippery one. In everyday research discourse, especially in the humanities and social sciences, we often talk about “large-scale” or “small-scale” projects to describe the scope or extent of inquiry: global, regional, local. We might think about this notion of scale as analytical scale — it shapes the framing of your research questions and the granularity of the data you collect. It also relates to data resolution: are you mapping countries, cities, buildings, or rooms? For example, a scholar analyzing the spread of Renaissance humanism might study its trans-European intellectual movement at a continental scale, but zoom into a city like Florence or Leuven to trace correspondence networks or map printers’ workshops.

There are different analytical scales:

• A macro-scale project might map slave trade routes across the Atlantic.
• A meso-scale analysis could examine plantation systems in the Caribbean.
• A micro-scale study might analyze the spatial layout of a single plantation to understand labor organization and resistance.

But in GIScience, “scale” has a more specific and technical meaning: it refers to the mathematical relationship between distances on a map and actual distances on the ground. This is known as cartographic scale, and it’s expressed as a ratio — for example, 1:50,000 (where 1 unit on the map represents 50,000 units in the real world).

Here's where the confusion arises:

• A large-scale map (e.g., 1:5,000) shows a small area in great detail — like a campus or neighborhood.
• A small-scale map (e.g., 1:5,000,000) shows a large area with less detail — like an entire continent.

Exercise: Interpreting Different Scales

Exercise: Why Scale Matters

Applying the Humanities Lens

If you’re working on a particular project (if not, take a moment to conceptualize a potential humanities project), try articulating scale in both senses for this project. What spatial extent are you working with, and at what level of detail. A map of various medieval manuscripts’ journeys throughout Europe, across space and through time, might be small in cartographic scale, but large in terms of narrative ambition and analytical scale.

References

• Burrough, P., McDonnel, R. & Lloyd, C. (2015) Principles of Geographical Information Systems (3rd ed.) Oxford: Oxford University Press