I was reminded by that bizarre NYT opinion piece that interdiscplarity is all the rage, but people rarely talk about intradisciplinarity. How big is the discrepancy? Well, Google had about 27,500 documents for me when I search intradisciplinary, and over 17,000,000 for interdisciplinary -- over 600:1. (Naturally, Google suggested that I meant interdisciplinary when I searched for intradisciplinary.) On Google Scholar, it's still over 100:1; 4,050 to 697,000.
I'm a big fan of intradisciplinary work. I enjoy working with computer scientists (and EE people, who I'll add in the mix, as we're often working on the same problems) in a range of areas on different types of problems. I've designed my graduate class in networking algorithms to bring together systems and theory, with papers from both sides of the aisle represented. I find one of the benefits of being in a smaller department at Harvard is that it promotes intradisciplinary work, because you talk to a more varied mix of people.
I wish there was more attention given to intradisciplinary work, because from my standpoint, it's important and useful. It's great when computer science can influence the direction of biology, economics, and physics; but I think we also get amazing payoffs when networking people and theory people and machine learning people and architecture people work together too. While it does happen, and non-trivially frequently, thank goodness, on the whole I think the community could do a bit more to promote that kind of work.
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4 comments:
Universities value interdisciplinary research more in theory than in practice (just like teaching). Everyone needs to write papers that can be published in their own field. If you're in computer science, sure, have a chemist co-author a paper, as long as you can get your paper published in a computer science journal. Typically papers published in journals outside your discipline either don't count or count less than papers in your discipline when it comes time for tenure review.
A lot of interdisciplinary articles fall through the editorial cracks. For example, I've seen articles rejected because they're too statistical for a medical journal, and too medical for a statistical journal.
The discrepancy between the two is probably much smaller than what you make it out to be: interdisciplinary is a word, while intradisciplinary is not (source: OED). By definition, all work that is not interdisciplinary is "intradisciplinary", hence "intradisciplinary" is just the default.
One of the requirements for candidacy at UMass CS is the completion of a "synthesis project" which combined 2 areas of computer science (e.g. AI-Systems, Systems-Theory). More information here.
Intra-disciplinary research often has the same issues as inter-disciplinary work in terms of lack of natural venues. For example, a somewhat technical work that improves an algorithm marginally in theory but significantly in practice may be uninteresting to a theory audience, and may have too many greek symbols for a more applied audience.
While inter-disciplinarity of a work may these days be considered cool enough to make it publishable, intra-disciplinary work does not often have this coolness factor. So I am thankful for this post. Hopefully it contributes to making intra-disciplinary research cool too.
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