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|Publication type:||Conference paper|
|Type of review:||Peer review (publication)|
|Title:||Towards an ethical code for data-based business|
|Proceedings:||2019 6th Swiss Conference on Data Science (SDS)|
|Conference details:||6th Swiss Conference on Data Science (SDS), Bern, 14. Juni 2019|
|Publisher / Ed. Institution:||IEEE|
|Subjects:||Digital ethics; Data science|
|Subject (DDC):||005: Computer programming, programs and data |
|Abstract:||In this paper, we outline the structure and content of a code of ethics for companies engaged in data-based business, i.e. companies whose value propositions strongly depends on using data. The code provides an ethical reference for all people in the organization who are responsible for activities around data. It is primarily targeting private industry, but public organizations and administrations may also use it. A joint industry-academic initiative, involving specialists for ethics as well as for all relevant data-related issues, developed this code.|
|Fulltext version:||Accepted version|
|License (according to publishing contract):||Licence according to publishing contract|
|Departement:||School of Engineering|
|Organisational Unit:||Institute of Data Analysis and Process Design (IDP)|
|Appears in collections:||Publikationen School of Engineering|
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|2019_Heitz_Towards an ethical code for data-based business_IEEE.pdf||360.93 kB||Adobe PDF|
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Loi, M., Heitz, C., Ferrario, A., Schmid, A., & Christen, M. (2019). Towards an ethical code for data-based business. 2019 6th Swiss Conference on Data Science (SDS). https://doi.org/10.1109/SDS.2019.00-15
Loi, M. et al. (2019) ‘Towards an ethical code for data-based business’, in 2019 6th Swiss Conference on Data Science (SDS). IEEE. Available at: https://doi.org/10.1109/SDS.2019.00-15.
M. Loi, C. Heitz, A. Ferrario, A. Schmid, and M. Christen, “Towards an ethical code for data-based business,” in 2019 6th Swiss Conference on Data Science (SDS), 2019. doi: 10.1109/SDS.2019.00-15.
Loi, Michele, et al. “Towards an Ethical Code for Data-Based Business.” 2019 6th Swiss Conference on Data Science (SDS), IEEE, 2019, https://doi.org/10.1109/SDS.2019.00-15.
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