返回
Research-ready data: the C-Surv data model
DOI:10.1007/s10654-022-00916-y.png)
摘要
En 中文
Research-ready data (data curated to a defined standard) increase scientific opportunity and rigour by integrating the data environment. The development of research platforms has highlighted the value of research-ready data, particularly for multi-cohort analyses. Following stakeholder consultation, a standard data model (C-Surv) optimised for data discovery, was developed using data from 5 population and clinical cohort studies. The model uses a four-tier nested structure based on 18 data themes selected according to user behaviour or technology. Standard variable naming conventions are applied to uniquely identify variables within the context of longitudinal studies. The data model was used to develop a harmon-ised dataset for 11 cohorts. This dataset populated the Cohort Explorer data discovery tool for assessing the feasibility of an analysis prior to making a data access request. Data preparation times were compared between cohort specific data models and C-Surv.It was concluded that adopting a common data model as a data standard for the discovery and analysis of research cohort data offers multiple benefits.
Keyword:
PARKINSON DISEASE
COHORT PROFILE
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.9
论文数:
3.7K
被引数:
1.6W
机构
引用论文
UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age英国生物银行: 一个开放获取的资源,用于识别各种复杂的中老年疾病的原因
PLOS MEDICINE
IF9.9

