方舟：一款用于健康与医学研究的可定制化网络数据管理工具。

The Ark: a customizable web-based data management tool for health and medical research.

作者信息

Bickerstaffe Adrian, Ranaweera Thilina, Endersby Travis, Ellis Christopher, Maddumarachchi Sanjaya, Gooden George E, White Paul, Moses Eric K, Hewitt Alex W, Hopper John L

机构信息

Centre for Epidemiology and Biostatistics, The University of Melbourne, Carlton, 3010, Australia.

Curtin UWA Centre for Genetic Origins of Health and Disease, Faculty of Health Sciences, Curtin University, Bentley, 6102, Australia.

出版信息

Bioinformatics. 2017 Feb 15;33(4):624-626. doi: 10.1093/bioinformatics/btw675.

DOI:10.1093/bioinformatics/btw675

PMID:28003258

Abstract

SUMMARY

The Ark is an open-source web-based tool that allows researchers to manage health and medical research data for humans and animals without specialized database skills or programming expertise. The system provides data management for core research information including demographic, phenotype, biospecimen and pedigree data, in addition to supporting typical investigator requirements such as tracking participant consent and correspondence, whilst also being able to generate custom data exports and reports. The Ark is 'study generic' by design and highly configurable via its web interface, allowing researchers to tailor the system to the specific data management requirements of their study.

AVAILABILITY AND IMPLEMENTATION

Source code for The Ark can be obtained freely from the website https://github.com/The-Ark-Informatics/ark/ . The source code can be modified and redistributed under the terms of the GNU GPL v3 license. Documentation and a pre-configured virtual appliance can be found at the website http://sphinx.org.au/the-ark/ .

CONTACT

adrianb@unimelb.edu.au.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

The Ark是一个基于网络的开源工具，它使研究人员无需专业的数据库技能或编程专业知识就能管理人类和动物的健康与医学研究数据。该系统为核心研究信息提供数据管理，包括人口统计学、表型、生物样本和谱系数据，此外还支持典型的研究者需求，如跟踪参与者的同意情况和通信记录，同时还能够生成定制的数据导出和报告。The Ark在设计上是“通用研究型”的，并且可以通过其网络界面进行高度配置，使研究人员能够根据其研究的特定数据管理需求定制该系统。