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More info on data collection

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  ### Data Collection and Management Plan
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- In the course of the BigCode project, we collected two main datasets. The primary training dataset is The Stack, which was obtained by gathering public code files, issues, and commits from GitHub through the BigQuery Service. Additionally, we collected a dataset of annotations of several kinds of private information on a subset of The Stack to support our privacy risk mitigation efforts.
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  The legal basis for data collection under fair use and with regards to GDPR and the corresponding case law are still evolving. In this context, the data collection and data management plans were carefully crafted with support from leading experts in the open source and legal tech community that participated in the Legal, Ethics, Governance Working Group in a best-effort approach to reflect current understandings of legal requirements for data collection and management.
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+ In the course of the BigCode project, we collected two main datasets. The primary training dataset is The Stack, which was obtained by gathering public code files, issues, and commits from GitHub. To collect Github repositories, we first extracted a list of repositories from [GHArchive](https://www.gharchive.org/) and subsequently cloned all of them using a large CPU cluster. We also used the data from GHArchive to extract the Github issues. The git commits were gathered from a public BigQuery service. Additionally, we collected a dataset of annotations of several kinds of private information on a subset of The Stack to support our privacy risk mitigation efforts.
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  The legal basis for data collection under fair use and with regards to GDPR and the corresponding case law are still evolving. In this context, the data collection and data management plans were carefully crafted with support from leading experts in the open source and legal tech community that participated in the Legal, Ethics, Governance Working Group in a best-effort approach to reflect current understandings of legal requirements for data collection and management.
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