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

How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?