数据科学家如何在科学合作中与领域专家合作：找到正确的答案还是提出正确的问题？
How Data Scientists Work Together With Domain Experts in Scientific Collaborations: To Find The Right Answer Or To Ask The Right Question?
摘要：
近年来，数据科学家和领域专家合作解决复杂科学问题的趋势越来越明显。然而，这种合作往往面临挑战。在本文中，我们的目标是通过半结构化的访谈研究来解读这种合作的复杂性，其中有22名受访者来自与数据科学家合作的生物医学科学家团队。在分析中，我们采用Olsons在Distance Matters中提出的四个维度框架来编码采访记录。我们的研究结果表明，除了在协作准备，技术准备和耦合的工作维度的故障，存在于共同基础建设过程中的紧张关系影响的协作结果，然后坚持在实际的协作过程。与以往著作对建立高水平共同点的一般性描述不同，在这一过程中，内容共同点的打破和过程共同点的强化更有利于科学发现。我们讨论了为什么会这样，设计建议是什么，并总结了未来的方向和限制。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
