The Information Schools, also referred to as iSchools, have a unique approach to data science with three distinct components: human‐centeredness, socially responsible, and rooted in context. In this position paper, we highlight and expand on these components and show how they are integrated in various research and educational activities related to data science that are being carried out at iSchools. We argue that the iSchool way of doing data science is not only highly relevant to the current times, but also crucial in solving problems of tomorrow. Specifically, we accentuate the issues of developing insights and solutions that are not only data‐driven, but also incorporate human values, including transparency, privacy, ethics, fairness, and equity. This approach to data science has meaningful implications on how we educate the students and train the next generation of scholars and policymakers. Here, we provide some of those design decisions, rooted in evidence‐based research, along with our perspective on how data science is currently situated and how it should be advanced in iSchools.

中文翻译：

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iSchool的数据科学方法：以人为本，对社会负责和上下文驱动

信息学校，也称为iSchools，具有独特的数据科学方法，包括三个不同的组成部分：以人为中心，对社会负责和植根于环境。在本立场文件中，我们重点介绍并扩展了这些组件，并展示了它们如何集成到iSchools正在进行的与数据科学相关的各种研究和教育活动中。我们认为，iSchool进行数据科学的方式不仅与当前高度相关，而且对于解决明天的问题也至关重要。具体来说，我们着重于发展洞察力和解决方案的问题，这些见解和解决方案不仅是由数据驱动的，而且还融合了人类价值，包括透明度，隐私，道德，公平和公平。这种数据科学方法对我们如何教育学生和培训下一代学者和决策者具有重要意义。在这里，我们提供了一些基于基于证据的研究的设计决策，以及我们对数据科学当前位置以及在iSchools中应如何发展的观点。