Paulina explored archaeological data literacy through historical maps in a short lecture and summarizes it in this article.
Recently, the Data Literacy Program’s (DLP’s) Paulina Przystupa gave a guest lecture on historical maps. While the DLP talks a lot about archaeological data, we often default to data tables as their main format. We allude to other kinds of structured data (such as sentences and citations) but an important type of structured data that we haven’t discussed much are maps. With the inspiration from that class, in this article we’re going to explore the five components of data literacy through the lens of maps.
Maps are data structures just like forms, notes, and tables because they are a way that we turn our observations into a standardized output. They’re also (like forms, notes, data tables, etc.) standardized by how the communities we participate in recognize what a map looks like. They also often require a certain patience, skill, or interest to use them well. Exploring maps from different places and periods gives us insight into the ways people structure observations when where those insights occur matters.
When we teach about data literacy and construct our Data Story series, we separate the ability to be data literate (and specifically archaeologically data literate) into the components of being able to read, work with, analyze, argue, and communicate with data. Maps, as a data structure, both cultivate archaeological data literacy and require us to use those data literacy skills.
You can get a lot of useful historical maps from the Library of Congress, like Sanborn Fire Insurance maps. This is a screen capture from “Introduction to the Collection” by the Library of Congress from in the public domain.
Reading map data, and map reading at all, is a skill. Everyone knows who in their family was not allowed to read the map on a road trip. To read maps well, one has to read the words within that map and understand how that abstraction–either as a physical or digital representation—relates to the real world. Maps also display relationships that other data structures, such as tables, are not equipped to do. This is because maps incorporate visual relationships. The closest thing to this in a table is if items closer to the headings are entered more recently than those below, demonstrating time rather than space. However, that is not always true.
The most common way that we work with maps in modern archaeological studies is through geographic information systems (GIS). GIS allow us to layer information from multiple sources (including databases and multiple maps) into the same interface. However, the foundations of GIS come from tangible ways we used to work with maps. Layering physical maps of the same scale allowed us to explore things without the use of a digital environment, just like one would compare photos.
GIS are also how we typically analyze maps. Most GIS platforms allow us to create complex spatial statics, calculating things like where, how densely, and what items cluster. However, we can also analyze maps’ makers, extents, and the period they represent. These aspects are important for tracing the provenance of and establishing the metadata for maps. Those observations allow us to say something about the process of map creation, turning those metadata into data by asking different questions.
Here’s an example of a map-based archaeological data visualization. This is a screen capture from “Welcome to Open Context” by Open Context from their website with this iteration used with permission / Cropped. The base map is Leaflet | Mapbox.com Copyrighted.
Maps are also a great way to argue with data because they’re already a data visualization. You can zoom in on a map to examine clustering and look at how changing scale disproves different arguments. However, maps can also “lie” because they’re abstractions of reality. Because they represent something three-dimensional in a two-dimensional way (in most cases), they only preserve certain features of reality. If this interests you, we suggest you check out discussions around map projections. For example, just because something looks bigger on a map, doesn’t mean that’s always the case or, at least, not in the magnitude depicted.
However, just because more people can make maps now doesn’t mean that they should. Maps as data visualizations require skill to communicate well. Furthermore, with the proliferation of standard styles through GIS, many folks have lost the artistry and attention to communication that came with map-making. People often use the default settings in GIS software, leaving in unnecessary pieces (such as labeling the legend “Legend”) without considering their communicative value.
Regardless, maps allow people to see patterns unique ways. Their visual nature captures people’s interests because they use shapes, symbols, and relationships in a way that already seems to tell a story. Albeit one with a lot of caveats if you’re data literate!
We hope that this introduction to archaeological data literacy through examples from maps helps you understand the importance and value of maps in archaeology. They’re an awesome way to explore and cultivate data literacy in a lot of fields, and one that can begin by just digging out that old AAA map from the side door of your car! So next time you look at a map, consider what structures and standards it uses to convey its intended meaning and if it’s going to get you where you want to go.
