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图书馆的可复制性黑卡通:将学生与大学研究联系起来,并测试已发布代码的寿命
Chasz Griego1, Kristen Scotti1, Elizabeth Terveen2
1University Libraries, Carnegie Mellon University, Pittsburgh, Pennsylvania, 15213, USA.
F1000Research
|October 9, 2025
概括
在学术图书馆举行的黑客马拉松成功展示了计算研究中的可重复性. 参与者重新使用数据和代码,使用诸如Code Ocean和ChatGPT等工具来帮助故障排除,突出了图书馆支持开放科学的途径.
科学领域:
- 计算科学 计算科学
- 数字人文学科 数字人文学科
- 开放科学是一个开放的科学.
背景情况:
- 可重现性是计算科学中的一个关键挑战,影响科学完整性.
- 开放科学运动正在获得引力,学术图书馆发挥着关键作用.
- 卡内基梅隆大学图书馆的开放科学和数据协作 (OSDC) 计划通过各种举措促进开放科学.
研究的目的:
- 解决可复制计算研究的需求,促进开放科学.
- 组织一个以重复性为重点的黑卡通,使用真实研究成果来重复性.
- 评估不同平台和工具在促进研究可重复性的有效性.
主要方法:
- 组织了一个为期一天的黑客马拉松,以重复性为中心,邀请社区成员.
- 利用Python代码和数据从一个出版物存储在哈佛数据宇宙.
- 在Code Ocean中使用了一个计算囊,并探索了ChatGPT的故障排除代码错误.
主要成果:
- 学生们成功地复制了大多数数据可视化,对于已经过时的图书馆,需要进行一些手动调整.
- 代码海洋被证明是一个可访问的平台,减轻折旧风险.
- 聊天GPT协助识别和解决在代码重启期间遇到的问题.
结论:
- 黑客马拉松为学生提供了评估计算研究可重现性的实践经验.
- 与教师的合作增强了开放式研究材料,并突出了可重复性挑战.
- 这个案例研究为学术图书馆提供了一个模型,让他们的社区参与开放科学实践.
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