Archaeologists routinely create and use data, but they rarely talk about how they work with data. As a profession, we need to be more open and share our experiences and frustrations in working with data.
A field school is an excellent place to start these conversations. Through active participation in the practice of archaeology, many students begin to enter the profession through field schools.
The UC Berkeley Archaeological Research Facility (abbreviated as ARF, thankfully NOT abbreviated as UCBARF) launched a new field school. The ARF field school specifically serves students that need professional experience in archaeology but have financial or other restrictions that would prevent them from traveling to a project outside of the San Francisco Bay Area.
As a guest lecturer for this field school, I explored some of the challenges of working with data (see slides). We discussed why archaeologists create structured data (information organized to facilitate quantification and other computer analysis). We raised some of the methodological and ethical challenges involved in making structured data. Last, we looked at how we use both structured and unstructured (narrative) data. In practice, both play a role in shaping our understanding of the archaeological past.
After introducing some of the big picture issues, we got into some of the practicalities and specifics in how to read a dataset with the eye of an editor. This lets us focus on issues that may arise if one encounters some common problems in structured archaeological data such as:
- problems that may arise if we don’t have a good way of handling multiple values for a given attribute;
- problems if we were inconsistent in naming things;
- or problems if we didn’t have clear ways of expressing uncertainty.
We wrapped up by talking about the importance of clearly and unambiguously naming and identifying things. This is especially important when we need to describe and express relationships of archaeological context. If we’re not clear in how we identify and name each given stratigraphic deposit and feature, then we risk losing the contextual information in our data. That’s a big deal and a major challenge in archaeology. Without context as a guide, we lose our map for understanding any meaning in our data.
A schematic illustration showing how consistent identifiers for archaeological context mean we can link together data about bones, coins, and stratigraphy
I’m excited the ARF field school has made data such a priority of their program. I spent about an hour with the ARF field school and our colleague Paulina Przystupa led a three hour hands-on exploration of issues in interpreting data. It’s great to see data becoming more integral in archaeological professional development!