As an emerging field, data science has been applied to many disciplines. Universities and colleges are quickly developing data science programs. The development of the field of data science has introduced new ethical issues. However, data science ethics education has not been addressed by data science programs in higher education or industry.

The authors of this paper propose the key topics that should be covered in a data science curriculum by reviewing and analyzing 11 relevant codes of ethics and ethics frameworks. The authors’ analysis also confirms that neither the current Data Science Association’s Code of Conduct nor “the Association for Computing Machinery (ACM) code of conduct for computing professionals” sufficiently covers these key topics.

The authors’ contribution lies in their emphasis on the importance of a data science ethics education; their comprehensive literature survey and analysis of existing codes of ethics and ethics frameworks relevant to data science; and their proposed key concepts of data science ethics to be included in a data science curriculum. However, the description of the topics is at a very general and high level. A more detailed and in-depth discussion is needed for the topics to be included in a data science curriculum. Curriculum materials such as case studies and recommended readings are needed for teaching data science ethics. Details on how to address the gap between data science ethics and the ACM code can be explored.