In this chapter, we propose a non-traditional RCR training in data science that is grounded into a virtue theory framework. First, we delineate the approach in more theoretical detail, by discussing how the goal of RCR training is to foster the cultivation of certain moral abilities. We specify the nature of these abilities: while the ideal is the cultivation of virtues, the limited space allowed by RCR modules can only facilitate the cultivation of superficial abilities or proto-virtues, which help students to familiarize with moral and political issues in the data science environment. Third, we operationalize our approach by stressing that (proto-)virtue acquisition (like skill acquisition) occurs through the technical and social tasks of daily data science activities, where these repetitive tasks provide the opportunities to develop (proto-)virtue capacity and to support the development of ethically robust data systems. Finally, we discuss a concrete example of how this approach has been implemented. In particular, we describe how this method is applied to teach data ethics to students participating in the CODATA-RDA Data Science Summer Schools.

翻译：在本章中，我们提出一种基于美德伦理框架的非传统负责任研究行为（RCR）训练方案，适用于数据科学领域。首先，我们从理论层面详细阐述该方法，探讨RCR训练的目标在于培养特定道德能力。我们界定了这些能力的本质：理想状态是培育美德，但受限于RCR模块的有限空间，只能促进表层能力或前美德的培养——这有助于学生熟悉数据科学环境中的道德与政治议题。其次，我们通过强调（前）美德习得（如同技能习得）发生于日常数据科学活动的技术与社会任务中，将这些重复性任务视为发展（前）美德能力及支撑构建伦理稳健数据系统的契机，从而使该方法具备可操作性。最后，我们讨论该方法的具体实施案例，重点描述如何将其应用于CODATA-RDA数据科学暑期学校参与学生的数据伦理教学中。