This week, our Digital Methods course focuses in on an idea that I, as a doctoral student in forensic anthropology, think about so much, it creeps into my dreams. What do I mean, you ask? Data, of course! As a second year in the program, the count down to switching from course work to my dissertation research is getting shorter and shorter. With this thought in the back, side, and front of my mind, it feels like all I can think about is data. Where will I collect my data? Or, can I even collect my data any time soon? Will I be able to find enough data? What types of data should I collect? Will my data be representative of the populations I am interested in studying? (For context, I study skeletal data for identification purposes.) How will I analyze my data?…You get the picture.
Now that you have a better understanding for my slight obsession with data, you may understand why the articles this week made me take a step back for a moment and think about what really constitutes data – especially to those in the field of humanities. While I work with a lot of data, it is often in the form of something akin to measurements of skeletal elements, which are easily organized within a nice excel spreadsheet and can be analyzed via a series of statistical methods. It’s easy to think of my data as data because it reflects the idea of data that stems from hard science fields. And it’s easy to understand why, as everything is about data in forensic anthropology and how good data can be used to created identification methods that are valid, replicable, generally accepted in the field, and have known error rates. Methods that do not meet these rigorous standards cannot hold up in court settings and may invalidate an entire investigation.
However, my data extends beyond the numbers I collect via measurements or observation scores. In fact, data in the form of background research or contextual information are often overlooked by those in more scientific fields even though these data are used by those in humanities. Which is surprising because if we only treat data as numbers as data, we lessen our understanding of the data and what they mean. For example, in the realm of forensic anthropology, data are usually individuals from skeletal samples. But what is often left unexplored is the background information on those individuals that tell us more about why these individuals were donated to these collections, how they were donated, and how this has varied across time and by collection. This type of information is essential to our understanding of our project overall and cannot be understood via t-tests on the “raw” numerical data.
And while this data in the form of historical records may be harder in some ways to work with, as it must be conceptualized in a new way, it does not make it any less relevant to a study. In fact, it may make it more relevant as an analysis of why that data were included or how they were shaped can indicate important ramifications for any subsequent method produced. In this sense, tools used in digital humanities will be extremely impactful in the social science, as we can start to understand how to better analyze all of our data – and not just the data filling our countless excel sheets.
And so on that note, if you are looking for me over the next few months, I will most likely be found on my couch and in front of my laptop exploring the ways in which my historical research on skeletal collections can be analyzed using digital methods so that I can frame my work with any “standard” data down the line.
