  In recent years there has been an increasing trend in which data scientists
and domain experts work together to tackle complex scientific questions.
However, such collaborations often face challenges. In this paper, we aim to
decipher this collaboration complexity through a semi-structured interview
study with 22 interviewees from teams of bio-medical scientists collaborating
with data scientists. In the analysis, we adopt the Olsons' four-dimensions
framework proposed in Distance Matters to code interview transcripts. Our
findings suggest that besides the glitches in the collaboration readiness,
technology readiness, and coupling of work dimensions, the tensions that exist
in the common ground building process influence the collaboration outcomes, and
then persist in the actual collaboration process. In contrast to prior works'
general account of building a high level of common ground, the breakdowns of
content common ground together with the strengthen of process common ground in
this process is more beneficial for scientific discovery. We discuss why that
is and what the design suggestions are, and conclude the paper with future
directions and limitations.
