Developing an Online Data Ethics Module Informed by an Ecology of Data Perspective

Abstract

A self-perceived lack of training in ethical theories and related pedagogy has kept many engineering faculty members from teaching data ethics, an important aspect of engineering research that has become more salient in recent years. This paper describes the development of a module, which includes concepts, cases, policies, and best practices, to support the teaching of ethical data practice. Based on a user-oriented design approach and a moral literacy framework, the module was designed to be used in different courses and co-curricular activities for students of varying levels of competence to improve their ability to identify and analyze ethical problems associated with the handling of research data. This work seeks to encourage ethical reflection on researchers' data practice through the idea of an "ecology of data," which highlights the coproduction of data by multiple, interconnected, and heterogeneous actors. This paper also presents online and in-class evidence about the impact and limitations of the module, which is now available for interested researchers and instructors to browse and use.

Learning analytics as data ecology: a tentative proposal

“…(Also see Star & Ruhleder, 1996). This resembles Davenport and Prusak's (1997) description which refers to "information ecology", and also Baker and Bowker's (2007) case study which highlights the mediating function of data in tying together a complex web of standards, relationships, and professional organizations (in Tang, et al, 2022). The range of human actors in a data ecology includes data curators, data submissions, support assistance, and data flow engineers (Nadim, 2016).…”

“…The notion of a data ecology also highlights the roles of governments and industry and the understanding of big data within the "larger ecology of markets, organizations, usage, culture, and the production of services" (Shin, 2016, p. 845) as well as consideration of what constitutes a socio-technical system. Data ecologies might be understood as might be understood as a heterogeneous and organic system made up of the multiple ways that people, institutions, technology, and non-human actors exchange information and values (Tang, et al, 2022). (Also see Star & Ruhleder, 1996).…”

“…In their article, Tang et al (2022) describe the potential of how data generated in one context or in response to a data query can enter new research and development lifecycles long after the completion of the original study. Queenborough et al (2010) call this an "ecology of data-sharing", and Sauvé and Houben (2021) "an ecology of interconnected data devices."…”