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Related to this point is the tension between breadth and depth. Should an individual trained in X
who wishes to work at the intersection of X and Y undertake to learn about Y on his or her own, or seek
to collaborate with an individual trained in Y? Leading-edge research in any field requires deep knowl-
edge. But work at the interface of two disciplines draws on both of them, and it is difficult to be deep in
both fields; thus, Ph.D.-level expertise in both computer science and biology may be unrealistic to
expect. As a result, collaboration is likely to be necessary in all but extraordinary cases.
Thus, what is the right balance to be struck between collaboration and multiskilling of individuals?
There is no hard-and-fast answer to this question, but the answer necessarily involves some of both.
Even if “collaboration” with an expert in Y is the answer, the individual trained in X must be familiar
enough with Y to be able to conduct a constructive dialogue with the expert in Y, asking meaningful
questions and understanding answers received. At the same time, it is unlikely that an expert in X could
develop in a reasonable time expertise in Y comparable to that of a specialist in Y, so some degree of
collaboration will inevitably be necessary.
This generic answer has implications for education and research. In education, it suggests that
students are likely to benefit from presentations by both types of expert (in X and in Y), and the
knowledge that each expert has of the other’s field should help to provide an integrated framework for
the joint presentations. In research, it suggests that research endeavors involving multiple principal
investigators (PIs) are likely to be more successful on average than single-PI endeavors.
Stovepiping can also cause problems for graduate students who are interested in dissertation work,
although for graduate students these problems may be less severe than for faculty. Some universities
make it easier for graduate students to do interdisciplinary work by allowing a student’s doctoral work
to be supervised by a committee composed of faculty from the relevant disciplines. However, in the
absence of a thesis supervisor whose primary interests overlap with the graduate student’s work, it is
the graduate student himself or herself who must be the intellectual integrator. Such integration re-
quires a level of intellectual maturity and perspective that is often uncommon in graduate students.
The course of graduate-level education in computing and in biology is different in some ways. In
biology, students tend to propose thesis topics earlier in their graduate careers, and then spend the
remainder of their time doing the proposed research. In computer science (especially more theoretical
aspects), in contrast, proposals tend to come later, after much of the work has been done. Computer
science graduates do not usually obtain postdoctoral positions, more commonly moving directly to
industry or to a tenure-track faculty position. Receiving a postdoctoral appointment is often seen as a
sign of a weak graduate experience in computer science, making postdoctoral opportunities in biology
seem less attractive.
10.3.3.3 Coordination Costs
In general, the cost of coordinating research and training increases with interdisciplinary work.
When computer scientists collaborate with biologists, they also are likely to belong to different depart-
ments or universities. The lack of physical proximity makes it harder for collaborators to meet, coordi-
nate student training, and share physical resources, and studies indicate that distance has especially
strong effects on interdisciplinary research.^76
Recognizing the importance of reducing distances between collaborators, Stanford University’s
Bio-X program is designed specifically to foster communication campus-wide among the various disci-
plines in biosciences, biomedicine, and bioengineering. The Clark Center houses meeting rooms, a
shared visualization chamber, low-vibration workspace, a motion laboratory, two supercomputers, the
(^76) J. Cummings and S. Kiesler, KDI Initiative: Multidisciplinary Scientific Collaborations, report to National Science Foundation,
2003, available at http://netvis.mit.edu/papers/NSF_KDI_report.pdf; R.E. Kraut, S.R. Fussell, S.E. Brennan, and J. Seigel, “Un-
derstanding Effects of Proximity on Collaboration: Implications for Technologies to Support Remote Collaborative Work,” pp.
137-162 in Distributed Work, P.J. Hinds and S. Kiesler, eds., MIT Press, Cambridge, MA, 2002.