CAA2012 and research decision making
authored by Frank Lynam at 31/03/2012 14:33:09
I’m just back from CAA2012. CAA is the biggest conference that specifically deals with computing in archaeology and this year it was held at the University of Southampton. Archaeologists are fond of the computer approach and so the range of topics on display was broad and showed off a good deal of expertise and promise. It was a perfect few days personally in the sense that I am in the first year of my PhD and am still feeling about for that interesting research question. I know that it’s going to be in the area of archaeological data management but have not yet fully decided what exact flavour it will take. Should I continue to incorporate and pursue work I’ve done in the past in the field of digital visualisation? How about my work with immersive systems such as AR? Whether to go theory heavy or to focus on solving dataset-driven research questions using new digital methodologies? CAA2012 showed me two things that will greatly help me navigate my thought process through these considerations over the next few months. I was able to pick out the current flavour-of-the-month themes in archaeological computing and I identified the key movers and shakers in the field.
Picking your specific research topic is an interesting process in itself and deserves a bit of reflection. The general principle in academia seems to be that there are the big questions out there and everyone is aware of these but these all tend to be monopolised by the big names of the disciplines. This then leaves the much more specific topics for the less well known researchers and as such one can often find themselves conducting research in a corner of their field that few others besides themselves would either understand or, and more pertinently, have any interest in.
This is a somewhat depressing realisation and one that might inevitably lead to the conclusion that there are vast swathes of research that are entirely artificial if you define genuine research to be led from first principles by an authentic interest in the subject on the part of the researcher themselves. Once you artificially corral people into doing work in areas that they don’t really want to be working in then you undermine the entire system of knowledge production happening in the academy.
Therefore as a research student you have to be quite stubborn and determined in the path that you take. Supervisors might be telling you to go off and do research on Roman ceramics lamps from a site in southern Turkey when in fact all you want to do is become a marine archaeologist and spend your time diving off the coast of Cyprus. The former approach might ease your way through graduate school but in the end of the day you have to wake up every morning and look at yourself in the mirror.
CAA2012 allowed me to see what is currently going on in the field in lots of different areas: the semantic web, general data management, computer vision, photogrammetry, other forms of 3D data capture, and others. Now the challenge for me is to position myself within one or more of these ponds of investigation in a way that makes my work relevant to the general eco-system but is also in some significant way true to the type of work that I want to be doing.
There is a final complication that enters this decision making process and that is the idea that just because a theoretical or practical method is currently in vogue does that necessarily mean that it is the best way of going about achieving an end? So, for example, while Linked Open Data seems to be the current method of choice to tackle the problem of dealing with distributed and heterogeneous datasets, this does not mean to say that there is not another approach that might be better suited to tackle the issues at hand. Just because the majority of researchers favour a method does not necessarily mean that it is the best. However, adopting the ‘better’ approach for your own work might satisfy your need to be true to yourself but at the same time it could also isolate you from your research community. Decisions made in the early days of a PhD can therefore have far reaching and significant implications for the following years and should not be taken lightly.