Psych-DS: A FAIR data standard for behavioral datasets

Psych-DS：行为数据集的公平数据标准

• 批准号: 10645923
• 负责人: Melissa Kline
• 金额: $ 109.38万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10645923
• 关键词: Adopted; Adoption; BRAIN initiative; Behavioral; Behavioral Sciences; Biomedical Research; Brain; Brain imaging; Child; Cognitive; Communities; Computer software; Computers; Consensus; Data; Data Analyses; Data Collection; Data Set; Development; Documentation; FAIR principles; Feedback; Hand; Human; Individual; Infrastructure; Interruption; Language; Link; Measurement; Measures; Metadata; Mind; Names; Outcome; Persons; Psychologist; Public Health; Pythons; Questionnaires; Readability; Reading; Recommendation; Reproducibility; Research; Research Personnel; Science; Scientist; Specific qualifier value; Standardization; System; Translating; Translations; Update; Validation; Work; analysis pipeline; automated analysis; behavioral study; brain research; data format; data standards; design; experimental study; flexibility; functional MRI scan; improved; indexing; literacy; neural; neuroimaging; neurophysiology; open source tool; prevent; scientific organization; terabyte; tool

Summary: Behavioral data is central to biomedical research, including both synchronous measures (e.g. brain activation and button-presses from a reading task in an fMRI scan), and those performed independently (e.g. a literacy questionnaire.) Compared to neurophysiology and brain imaging data, behavioral data is often relatively small, with file sizes in the megabytes rather than terabytes for both experimental scripts and resulting datasets. The key challenge for behavioral data is not size but variability: many studies are not designed with FAIR (Findable, Accessible, Interoperable, and Reusable) sharing or automated analysis pipelines in mind. Those that are machine-readable lack common standards of format, organization, or documentation across labs or even individual studies. We propose to implement a standard for human behavioral experiments in the BRAIN initiative using a community-developed data specification, Psych-DS. Because Psych-DS is designed to be similar to the raw data researchers already acquire, this work will result in a broad pool of users adopting the standard without additional effort or interruption to existing workflows; feedback from these researchers will be central to development of all three aims of the proposal: First, we will create validator software for Psych-DS datasets, to ensure that tools implementing the standard remain cross-compatible for researchers using a variety of languages (Python, R, Javascript) as well as compiling datasets by hand. Second, the standard and validation packages will be integrated into at least three popular experiment presentation packages in wide use by psychologists and cognitive neuroscientists (jsPsych, PsychoPy, and Lookit/Children Helping Science). Third, to support projects that involve coordinated behavioral and neuroimaging/neurophysiological data, we will implement tools to translate between Psych-DS and the Brain Imaging Data Standard (BIDS). The lack of consensus around how behavioral data are organized prevents a broad and diverse swath of biomedically relevant research from being fully integrated with the infrastructures currently being built to support neuroscientific research at scale. Implementation and adoption of the Psych-DS standard will provide a machine-readable data format that can be used across a wide variety of research contexts, and lay the groundwork for further improvements to standardization and reproducibility in the biomedical and behavioral sciences.

概括： 行为数据是生物医学研究的核心，包括两种同步测量（例如大脑激活 在fMRI扫描中从阅读任务中进行按钮 - 以及独立执行的任务（例如，识字能力 问卷。）与神经生理学和脑成像数据相比，行为数据通常相对较小， 具有兆字节的文件大小，而不是用于实验脚本和结果数据集的terabytes。这 行为数据的关键挑战不是大小，而是可变性：许多研究不是公平设计的（可发现， 可以牢记可访问，可互操作和可重复使用的）共享或自动分析管道。那些 机器可读的格式，组织或文档的常见标准跨实验室甚至是 个人研究。 我们建议在大脑倡议中实施人类行为实验的标准 社区开发的数据规范，心理-D。因为Psych-DS的设计与RAW相似 数据研究人员已经获得了，这项工作将导致大量的用户在没有标准的情况下采用 现有工作流程的额外努力或中断；这些研究人员的反馈将是 提案的所有三个目标的发展： 首先，我们将为Psych-DS数据集创建验证软件，以确保实施标准的工具 使用各种语言（Python，R，JavaScript）以及 手工编译数据集。其次，标准和验证软件包将至少集成到三个 心理学家和认知神经科学家广泛使用的流行实验表现包 （JSpsych，Psychopy和Lookit/儿童帮助科学）。第三，支持涉及协调的项目 行为和神经影像学/神经生理学数据，我们将实施工具以在心理-D之间翻译 和大脑成像数据标准（BIDS）。 围绕如何组织行为数据缺乏共识，阻止了广泛而多样化 与目前正在构建的基础架构完全集成到的生物医学相关研究 大规模支持神经科学研究。 Psych-DS标准的实施和采用将提供 可以在各种研究环境中使用的机器可读数据格式，并放置 基础工作，以进一步改善生物医学和行为的标准化和可重复性 科学。