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December 02, 2014
Doing interdisciplinary work (Advice to young scholars, part 3 of 4)
These notes are an adapted summary of the the 3rd of 4 professional development panels for young scholars, as part of the American Mathematical Society (AMS) Mathematics Research Community (MRC) on Network Science, held in June 2014. Their focus was on mathematics, computer science, and networks, but many of the comments generalize to other fields. [1]
Panel 3. Interdisciplinary Research
Opening remarks: Sometimes, the most interesting problems come from interdisciplinary fields, and interdisciplinary researchers are becoming more and more common. As network scientists, we tend to fit in with many disciplines. That said, the most important thing you have is time; therefore, choose your collaborations wisely. Interdisciplinary work can be divided into collaboration and publication, and each of these has its own set of difficulties. A common experience with interdisciplinary work is this:
Any paper that aims for the union of two fields will appeal mainly to the intersection. -- Jon Kleinberg
- What's the deal with interdisciplinary collaborations? How do they impact your academic reputation?
There are three main points to consider when choosing interdisciplinary collaborations, and how they impact perceptions of your academic reputation.
First, academia is very tribal, and the opinions of these tribes with regards to your work can have a huge impact on your career. Some departments won't value work outside their scope. (Some even have a short list of sanctioned publication venues, with work outside these venues counting literally as zero for your assessments.) Other departments are more open minded. In general, it's important to signal to your hopefully-future-colleagues that you are "one of them." This can mean publishing in certain places, or working on certain classes of problems, or using certain language in your work, etc. If you value interdisciplinary work, then you want to end up in a department that also values it.
Second, it's strategically advantageous to be "the person who is the expert on X," where X might be algorithms or statistics or models for networks, or whatever. Your research specialty won't necessarily align completely with any particular department, but it should align well with a particular external research community. In the long run, it is much more important to fit into your community than to fit into your department, research-wise. This community will be the group of people who review your papers, who write your external letters when you go up for tenure, who review your grant proposals, who hire your students as postdocs, etc. The worst possible situation is to be community-less. You don't have to choose your community now, but it helps to choose far enough ahead of your tenure case that you have time to build a strong reputation with them.
Third, make sure the research is interesting to you. If your contribution in some interdisciplinary collaboration is to point out that an off-the-shelf algorithm solves the problem at hand, it's probably not interesting to you, even if it's very interesting to the collaborator. Even if it gives you an easy publication, it won't have much value to your reputation in your community. Your work will be compared to the work of people who do only one type of research in both fields, and might not look particularly good to any field.
Be very careful about potentially complicated collaborations in the early stages of your career. Be noncommittal until you're sure that your personalities and tastes in problems match. (Getting "divorced" from a collaborator, once a project has started, can be exhausting and complicated.) Being able to recognize cultural differences is an important first step to good collaborations, and moving forward effectively. Don't burn bridges, but don't fall into the trap of saying yes to too many things. Be open to writing for an audience that is not your primary research community, and be open to learning what makes an interesting question and a satisfying answer in another field. - What's the deal with publishing interdisciplinary work? Where should it go?
As a mathematical or computer or data scientist doing work in a domain, be sure to engage with that domain's community. This helps ensure that you're doing relevant good work, and not reinventing wheels. Attend talks at other departments at your university, attend workshops/conferences in the domain, and discuss your results with people in the domain audience.
When writing, vocabulary is important. Knowing how to speak another discipline's language will help you write in a way that satisfies reviewers from that community. Less cynically, it also helps the audience of that journal understand your results, which is the real goal. If publishing in the arena of a collaborator, trust your collaborator on the language/writing style.
In general, know what part of the paper is the most interesting, e.g., the mathematics, or the method or algorithm, or the application and relationship to scientific hypotheses, etc., and send the paper to a venue that primarily values that thing. This can sometimes be difficult, since academic tribes are, by their nature, fairly conservative, and attempting to publish a new or interdisciplinary idea can meet with knee-jerk resistance. Interdisciplinary journals like PLOS ONE, which try not to consider domain, can be an okay solution for early work that has trouble finding a home. But, don't overuse these venues, since they tend also to not have a community of readers built in the way regular venues do.
Note: When you interview for a faculty position, among the many questions that you should be asking the interviewing department: "In practice, how is your department interdisciplinary? How do you consider interdisciplinary work when evaluating young faculty (e.g., at tenure time)?"
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[1] Panelists were Mason Porter (Oxford), David Kempe (Southern California), and me (the MRC organizers), along with an ad hoc assortment of individuals from the MRC itself, as per their expertise. The notes were compiled by MRC participants, and I then edited and expanded upon them for clarity and completeness, and to remove identifying information. Notes made public with permission.
[2] Here is a complete copy of the notes for all four panels (PDF).
posted December 2, 2014 03:40 AM in Simply Academic | permalink