Data Science Core

数据科学核心

基本信息

批准号：
10670075
负责人：
Richard C Gerkin
金额：
$ 10.69万
依托单位：
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-09-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10670075
关键词：
Abnormal coordination Adopted Algorithms Anatomy Biomedical Research Categories Code Communities Data Data Analyses Data Collection Data Science Core Data Set Dependence Documentation Dorsal Ensure Ethology Experimental Designs Freezing Fruit Future Genetic Genomics Goals Human Individual Knowledge Licensing Methods Modeling Morphologic artifacts Neurons Neurosciences Odors Outcome Output Performance Physiological Physiology Psychophysics Pythons Records Regional Anatomy Reproducibility Research Research Design Rodent Services Signal Transduction Smell Perception Source Code Specific qualifier value Standardization Statistical Data Interpretation Statistical Models Stimulus Surface System Technology Testing Time Work cell type climate science cost data integration data reduction data repository data sharing design experience experimental analysis experimental study falls high dimensionality high energy physics mathematical model multiscale data olfactory bulb open data open source opportunity cost optical imaging receptive field software development web services

项目摘要

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.

生物医学研究经历了可重复性的危机，由于缺乏协调性而加剧研究小组，弱研究设计，不透明算法以及不愿分享研究成果努力。但是近年来已经开始了解决这一危机的开始，重点是集成在实验室中，标准化，严格的统计分析，开源代码以及数据共享以及方法。该建议旨在“破解嗅觉代码”，这是一个深远的目标，需要公司致力于严格的开放科学原则。该提案的数据科学核心（DSC）反映了计划以三种主要方式满足这一承诺：（1）DSC将紧密协调数据的集成在提案的五个科学项目中，利用标准和采用技术来实现总可重复性在所有发现中，并确保所有研究输出都将被全面且可理解向公众使用；（2）DSC将与项目负责人合作，使用统计模型，节省时间和金钱，同时增加科学推断；（3）DSC将标准化跨项目刺激刺激，并创建一项服务，以将这一标准推向更大的研究社区，确保我们的努力可以直接告知未来的研究工作，并可以告知每个研究其他。