Journal article
“Ethics when you least expect it”: a modular approach to short course data ethics instruction
- Abstract:
- Data science skills are rapidly becoming a necessity in modern science. In response to this need, institutions and organizations around the world are developing research data science curricula to teach the programming and computational skills that are needed to build and maintain data infrastructures and maximize the use of available data. To date, however, few of these courses have included an explicit ethics component, and developing such components can be challenging. This paper describes a novel approach to teaching data ethics on short courses developed for the CODATA-RDA Schools for Research Data Science. The ethics content of these schools is centred on the concept of open and responsible (data) science citizenship that draws on virtue ethics to promote ethics of practice. Despite having little formal teaching time, this concept of citizenship is made central to the course by distributing ethics content across technical modules. Ethics instruction consists of a wide range of techniques, including stand-alone lectures, group discussions and mini-exercises linked to technical modules. This multi-level approach enables students to develop an understanding both of “responsible and open (data) science citizenship”, and of how such responsibilities are implemented in daily research practices within their home environment. This approach successfully locates ethics within daily data science practice, and allows students to see how small actions build into larger ethical concerns. This emphasises that ethics are not something “removed from daily research” or the remit of data generators/end users, but rather are a vital concern for all data scientists.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, 1.0MB, Terms of use)
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- Publisher copy:
- 10.1007/s11948-020-00197-2
Authors
- Publisher:
- Springer Verlag
- Journal:
- Science and Engineering Ethics More from this journal
- Volume:
- 26
- Pages:
- 2189–2213
- Publication date:
- 2020-02-17
- Acceptance date:
- 2020-02-10
- DOI:
- EISSN:
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1471-5546
- ISSN:
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1353-3452
- Pmid:
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32067185
- Language:
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English
- Keywords:
- Pubs id:
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1090357
- Local pid:
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pubs:1090357
- Deposit date:
-
2020-04-29
Terms of use
- Copyright holder:
- Bezuidenhout et al.
- Copyright date:
- 2020
- Rights statement:
- Copyright © 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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