Ruhamyankaka Emmanuel, Brunk Brian P, Dorsey Grant, Harb Omar S, Helb Danica A, Judkins John, Kissinger Jessica C, Lindsay Brianna, Roos David S, San Emmanuel James, Stoeckert Christian J, Zheng Jie, Tomko Sheena Shah
Infectious Diseases Research Collaboration, Kampala, Uganda.
Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Gates Open Res. 2020 Apr 6;3:1661. doi: 10.12688/gatesopenres.13087.2. eCollection 2019.
The concept of open data has been gaining traction as a mechanism to increase data use, ensure that data are preserved over time, and accelerate discovery. While epidemiology data sets are increasingly deposited in databases and repositories, barriers to access still remain. ClinEpiDB was constructed as an open-access online resource for clinical and epidemiologic studies by leveraging the extensive web toolkit and infrastructure of the Eukaryotic Pathogen Database Resources (EuPathDB; a collection of databases covering 170+ eukaryotic pathogens, relevant related species, and select hosts) combined with a unified semantic web framework. Here we present an intuitive point-and-click website that allows users to visualize and subset data directly in the ClinEpiDB browser and immediately explore potential associations. Supporting study documentation aids contextualization, and data can be downloaded for advanced analyses. By facilitating access and interrogation of high-quality, large-scale data sets, ClinEpiDB aims to spur collaboration and discovery that improves global health.
开放数据的概念作为一种增加数据使用、确保数据长期保存并加速发现的机制,正越来越受到关注。虽然流行病学数据集越来越多地存放在数据库和资源库中,但获取数据的障碍仍然存在。ClinEpiDB是利用真核病原体数据库资源(EuPathDB;一个涵盖170多种真核病原体、相关物种和选定宿主的数据库集合)广泛的网络工具包和基础设施,结合统一的语义网框架构建的临床和流行病学研究的开放获取在线资源。在这里,我们展示了一个直观的点击式网站,允许用户直接在ClinEpiDB浏览器中可视化数据并进行子集化处理,并立即探索潜在的关联。支持研究文档有助于进行背景分析,数据可以下载用于高级分析。通过促进对高质量、大规模数据集的访问和查询,ClinEpiDB旨在推动合作与发现,从而改善全球健康状况。