Linus Schumacher, contributor
Interdisciplinary collaboration is becoming more common and as such is changing the face of modern research. However, it comes with challenges that we are seldom trained for. This is something I experience myself and frequently hear from my peers. As a graduate student in mathematical biology, I collaborate closely with biologists who happen to work on other continents, thus spanning not just long geographical distances, but also the gap between maths and biology. Hopefully the challenges I will describe are applicable to other areas of science as well, but if not please do add you own perspectives in the comments.
When communicating with collaborators from another discipline, one challenge is language. I don’t mean the problem of two non-native English speakers (like myself) conversing in broken English – which can happen – I mean scientific language. Jargon can be a problem when communicating with the public, but also when communicating between scientists. It get’s worse when there are shared concepts with different discipline-specific names, or shared names for different concepts. For example, when mathematicians talk about a model, they mean a system of equations or a piece of code used for simulations. The biologist, when talking about a model might mean the mouse model for a human disease. And really they are both just talking about different representations of the same conceptual model (the hypothesis). Misunderstandings like this can go undetected for months at a time, hindering meaningful progress. I think that in the future more scientists will take on the role of translators between disciplines, or connectors. My colleague Jacob Scott has spoken about such issues before. These connectors will to some extent be jacks of all trades, and masters of none, but nonetheless vital to the efficiency of a scientific collaboration.
Stuck in the middle?
This new connector-niche presents an opportunity for pluripotent interdisciplinary researchers to stay undifferentiated, but also a risk of undetermined career fate decision. The problem is that we lack example career paths of these connectors’ that scientists in training can follow. With doctoral training in the UK increasingly under the umbrella of the Centres for Doctoral Training, we may be giving aspiring researchers an opportunity to nest themselves between the traditional disciplines. But I wonder if we then fail to prepare them for not quite feeling at home in any one department or discipline. As a trained physicist who is registered in the Department of Computer Science, while actually sitting in the Mathematical Institute working on biological problems, I know this feeling all too well.
To communicate with overseas collaborators I might have weekly, monthly or quarterly calls with some video calling software of my choice. The options vary in quality and usability, and some have better screen sharing or conferencing features than others. But essentially, none of them come close to meeting in person. I’ve made more progress meeting for two days on a transatlantic visit then I did in two months communicating over the Internet. Challenges extend to issues such as paper writing. Mathematicians mostly write in the typesetting language LaTeX, whereas our collaborators from the life sciences often use WYSIWYG word processing programs. Luckily, new tools have started to appear, that combine both ways of writing with shared access in the cloud. If I can get my collaborators to start using them, we might be able to cut out the back-and-forth emailing of documents all together.
It’s not you, it’s me.
The above may read like it’s only the biologists who have to learn to understand us mathematicians and to use the software we like. But I myself have got some homework to do, too. I have to come to grips with the breadth of biological knowledge, while not taking everything I read in a biological paper as established fact. Hypotheses and results in the literature may be unclear, disputed or plain wrong. But for me this harder to check than “going through the maths’’, so I need to build up a healthy scepticism. All too often I naively ask my collaborators about an only tangentially related paper and what impact it might have on our working hypothesis. Or I enthusiastically suggest experiments that quickly turn out to be near impossible, time-consuming or expensive to do.
What about the maths?
Even when I’ve mastered the understanding of the biological side of my collaborative work, it can be a whole other challenge to communicate the biology back to my mathematical peers. Without the relevance of the biological application, the mathematics can be so well established and simple that they may wonder why I’ve bothered with it. If they can even see the maths, that is. Increasingly the mathematics is so integrated with the biology that it all but disappears from the main body of a paper. This may be a good thing, as one of my supervisors often points out: Mathematics is just being used as one of many tools along the way to find new biology. Sometimes I feel like the most valuable contribution by a mathematician to a collaborative research effort can be the different way of thinking they bring to the table, and the conceptual insights that result from the cross-disciplinary discussion. Looking ahead, if that makes up more of our work in the future, how does one acknowledge or measure that contribution, other than by word of mouth? I don’t have an answer, but I hope we’ll find one by the time I graduate….