dc.contributor.author | Leonelli, S | |
dc.date.accessioned | 2016-09-13T12:58:13Z | |
dc.date.issued | 2016-11-14 | |
dc.description.abstract | The distributed and global nature of data science creates challenges for evaluating the
quality, import and potential impact of the data and knowledge claims being produced.
This has significant consequences for the management and oversight of responsibilities and
accountabilities in data science. In particular, it makes it difficult to determine who is
responsible for what output, and how such responsibilities relate to each other; what
‘participation’ means and which accountabilities it involves, with regards to data
ownership, donation and sharing as well as data analysis, re-use and authorship; and
whether the trust placed on automated tools for data mining and interpretation is
warranted (especially since data processing strategies and tools are often developed
separately from the situations of data use where ethical concerns typically emerge). To
address these challenges, this paper advocates a participative, reflexive management of data
practices. Regulatory structures should encourage data scientists to examine the historical
lineages and ethical implications of their work at regular intervals. They should also foster
awareness of the multitude of skills and perspectives involved in data science, highlighting
how each perspective is partial and in need of confrontation with others. This approach has
the potential to improve not only the ethical oversight for data science initiatives, but also
the quality and reliability of research outputs. | en_GB |
dc.description.sponsorship | This research was funded by the European Research Council grant award 335925 (“The
Epistemology of Data-Intensive Science”), the Leverhulme Trust Grant number RPG-2013-
153 and the Australian Research Council, Discovery Project DP160102989. | en_GB |
dc.identifier.citation | 28 December 2016, Vol. 374, Iss. 2083 | en_GB |
dc.identifier.doi | 10.1098/rsta.2016.0122 | |
dc.identifier.uri | http://hdl.handle.net/10871/23431 | |
dc.language.iso | en | en_GB |
dc.publisher | The Royal Society | en_GB |
dc.title | Locating Ethics in Data Science: Responsibility and Accountability in Global and Distributed Knowledge Production | en_GB |
dc.type | Article | en_GB |
dc.identifier.issn | 1471-2962 | |
dc.description | This is the author accepted manuscript. The final version is available from Royal Society via the DOI in this record. | |
dc.identifier.journal | Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | en_GB |