Gold, NE;
Krinke, J;
(2020)
Ethical Mining – A Case Study on MSR Mining Challenges.
In:
Proceedings of 17th International Conference on Mining Software Repositories (MSR ’20).
Association for Computing Machinery (ACM): Online (virtual conference).
(In press).
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Abstract
Research in Mining Software Repositories (MSR) is research involving human subjects, as the repositories usually contain data about developers’ interactions with the repositories. Therefore, any research in the area needs to consider the ethics implications of the intended activity before starting. This paper presents a discussion of the ethics implications of MSR research, using the mining challenges from the years 2010 to 2019 as a case study to identify the kinds of data used. It highlights problems that one may encounter in creating such datasets, and discusses ethics challenges that may be encountered when using existing datasets, based on a contemporary research ethics framework. We suggest that the MSR community should increase awareness of ethics issues by openly discussing ethics considerations in published articles.
| Type: | Proceedings paper |
|---|---|
| Title: | Ethical Mining – A Case Study on MSR Mining Challenges |
| Event: | 17th International Conference on Mining Software Repositories (MSR ’20) |
| Location: | Seoul, Republic of Korea |
| Dates: | 05 October 2020 - 06 October 2020 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3379597.3387462 |
| Publisher version: | https://2020.msrconf.org/ |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | research ethics, mining software repositories |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10093751 |
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