(超)主动数据整理:行为科学视频案例研究。

Journal of escience librarianship Pub Date : 2021-01-01 Epub Date: 2021-08-11 DOI:10.7191/jeslib.2021.1208
Kasey C Soska, Melody Xu, Sandy L Gonzalez, Orit Herzberg, Catherine S Tamis-LeMonda, Rick O Gilmore, Karen E Adolph
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引用次数: 0

摘要

视频数据非常适合研究再利用以及记录研究方法和研究成果。然而,对于社会和行为科学领域的研究人员来说,视频数据的整理是一个严重的障碍,因为在这些领域,行为视频数据是逐个会话获取的,数据共享并不是常态。为了消除在发表论文时(或之后)进行事后整理的繁重负担,我们介绍了主动数据整理的最佳实践--即在每次数据采集后立即整理和上传数据,以便随时按下按钮即可即时共享。事实上,我们建议研究人员采用 "超主动 "数据整理,公开分享研究过程中的每一步。Databrary 提供了必要的基础设施和工具--这是一个安全的网络数据图书馆,专为主动整理和共享可识别个人身份的视频数据及相关元数据而设计。在该项目中,数十名研究人员制定了一项共同协议,用于收集、注释和主动整理北美各地研究地点的婴儿和母亲在家中自然活动时的视频数据。PLAY 依靠可扩展的标准化工作流程来促进合作研究、确保数据质量,并为整个研究过程中的语料库共享和重用做好准备。
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(Hyper)active Data Curation: A Video Case Study from Behavioral Science.

Video data are uniquely suited for research reuse and for documenting research methods and findings. However, curation of video data is a serious hurdle for researchers in the social and behavioral sciences, where behavioral video data are obtained session by session and data sharing is not the norm. To eliminate the onerous burden of post hoc curation at the time of publication (or later), we describe best practices in active data curation-where data are curated and uploaded immediately after each data collection to allow instantaneous sharing with one button press at any time. Indeed, we recommend that researchers adopt "hyperactive" data curation where they openly share every step of their research process. The necessary infrastructure and tools are provided by Databrary-a secure, web-based data library designed for active curation and sharing of personally identifiable video data and associated metadata. We provide a case study of hyperactive curation of video data from the Play and Learning Across a Year (PLAY) project, where dozens of researchers developed a common protocol to collect, annotate, and actively curate video data of infants and mothers during natural activity in their homes at research sites across North America. PLAY relies on scalable standardized workflows to facilitate collaborative research, assure data quality, and prepare the corpus for sharing and reuse throughout the entire research process.

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