Data Science Core

生物医学研究经历了一场可重复性的危机，由于缺乏协调， 研究小组，薄弱的研究设计，不透明的算法，以及不愿意分享研究成果 努力但近年来，人们开始推动解决这一危机，重点是整合 跨实验室、标准化、严格的统计分析、开源代码和数据共享， 方法.这项提案旨在“破解嗅觉密码”，这是一个深远的目标，需要一家公司 坚持严谨、开放的科学原则。该提案的数据科学核心（DSC）反映了 我计划通过三个主要方面来实现这一承诺：（1）DSC将密切协调数据的整合 在该提案的五个科学项目中，利用标准和采用技术实现完全可重复性 所有研究结果，并确保所有研究成果都是全面和易懂的 （2）DSC将与项目负责人合作，使用以下方法优化数据收集决策： 统计模型，节省时间和金钱，同时增加科学推断;（3）DSC将标准化 气味刺激跨项目，并创建一个服务，推动这一标准到更大的研究 社区，确保未来的研究工作可以直接通过我们的努力，并可以告知每个 其他.

Biomedical research has experienced a crisis of reproducibility, exacerbated by lack of coordination between research groups, weak study designs, opaque algorithms, and an unwillingness to share the fruits of research efforts. But recent years have seen the beginning of a push to solve this crisis, with a focus on integration across labs, standardization, rigorous statistical analysis, open source code, and the sharing of data and methods. This proposal aims to “Crack the Olfactory Code”, a far-reaching goal that will require a firm commitment to rigorous, open science principles. The Data Science Core (DSC) for this proposal reflects a plan to meet this commitment in three major ways: (1) The DSC will tightly coordinate the integration of data across the proposal’s five scientific projects, utilizing standards and adopting technology for total reproducibility of all findings, as well as ensuring that all research outputs will be made comprehensively and intelligibly available to the public; (2) The DSC will work with project leaders to optimize data collection decisions using statistical models, saving time and money while increasing scientific inference; (3) The DSC will standardize odorant stimuli across projects and create a service for pushing this standard into the larger research community, ensuring that future research efforts can be directly informed by our efforts and can inform each other.