New Article: "Quantitative analysis of Munsell color data from archeological ceramics" Open Access!

My former student Lana Ruck and I have published an article on how to mathematically analyze Munsell color data. Although we use data from archaeological ceramics as our prime example, the method would work with any body of Munsell color data that was collected to address a hypothesis. The colors could be from soils, minerals, leaves, flowers, birds, and so forth, and the method would still work. We're so convinced that this article will be of wide interest that we paid for open access.

The idea is that you convert the Munsell readings to spatial coordinates in the Munsell color space and then perform spatial or statistical analyses on the coordinates, which are interval scale variables. For the kinds of hypotheses I wanted to test--whether the ceramic colors from one houselot or cluster of houselots were the same as those from another--I decided that logistic regression was probably the right technique because:

• the dependent variable (the provenience, i.e., the houselot of cluster of houselots) was a categorical variable; and
• the data were demonstrably non-normal, thus eliminating linear discriminant analysis.

I've been struggling with the issue of how to analyze this kind of data ever since I got back from Mayapan in 1992 or 1993 with thousands of Munsell observations and realized that I didn't know how to perform statistical tests on them. My best guess is that I finally figured out how to do it right, at least in theory, around 2006 or 2007, but it wasn't until a couple of years ago that Lana came along and mastered the logistic regression.

Apparently, the real lesson here is that if you think about something for 20 years, you just might figure out the answer, although I hasten to point out that during those 20 years I studied quantitative techniques pretty intensively.  I wasn't just sitting on the beach pondering the problem solely in thought; I was actually educating myself--howsoever unsystematically--about the general topic of mathematics in archaeology. Nevertheless, there is a push among university administrators to systematize and quantify scientists' goals and productivity. So, if I put down on my annual assignment that I'm going to study how to analyze Munsell colors, presumably I'm expected to produce the article in the year it's listed. If you take into account how long it took to devise the original research design, excavate the artifacts, and record the Munsell colors, this article has been in the works for 25 years! Should I submit a 25-year plan as part of my annual assignment? If I do, I can probably say anything I want because I'll almost certainly be dead in 25 years.

Here is the reference, linked to the article:

Ruck, Lana and Clifford T. Brown (2015). Quantitative analysis of Munsell color data from archeological ceramics. Journal of Archaeological Science: Reports 3:549-557. 

Just in case the link doesn't work for any reason, here is the URL: http://www.sciencedirect.com/science/article/pii/S2352409X15300730#

Enjoy!

As always, comments welcome.

Reflections on the Quantitative Methods and Computer Applications in Archaeology conference

The CAA conference was interesting, and I’m glad I went. I would have had more fun if I had figured out that they were serving lunch to everyone. I only noticed that the last day, and even on that occasion I missed the food because I stopped to chat with a graduate student. It was during the one (foodless) lunch I attended that I ran into a couple of people I know. If I had known they were there, I would have enjoyed the conference more because I would have had friends to hang out with. As it was, the conferees were mainly Europeans. Few Americans attended. It’s natural that geographic proximity would influence turnout, if only for economic reasons—my airline tickets were quite expensive—but it made the conference feel a little parochial, Roman this, Roman that.

The conference also felt a little narrow intellectually. I am probably only projecting my preferences—or prejudices—but the conference was heavy on GIS, and light by comparison on everything else. A lot of the papers and posters seem to me to be saying, “Hey, look at the cool, whizz-bang thing I can do with GIS!” I have nothing against GIS; on the contrary, I think GIS is crucial in archaeology. Because most of our data have a fundamental, primordial spatial component, GIS is the natural way for us to store, retrieve, analyze, visualize, and report our data. My own paper described research that we mostly performed within a GIS environment. Our research also would have been extraordinarily difficult to do in any other way. That said, I still think that GIS is basically a tool rather than an end in itself. Yet I came away with the impression that more than a few papers focused on showing the researchers’ technical mastery of GIS than actually contributing something substantively original. Sometimes I found myself saying, sotto voce, “It’s great that you can do that in GIS, but why would you? It’s so difficult and idiosyncratic that’s it’s not of broad interest.”

I hope in the future that the CAA gives at least a little more weight to Quantitative Methods and even non-GIS Computer Applications. I’m not blaming the organizers, who must content themselves with the papers that are submitted, and therefore do not have total control over their own agenda. But perhaps more could be done to encourage a broader range of contributions.