Stöhr Mark R, Majeed Raphael W, Günther Andreas
UGMLC, German Center for Lung Research (DZL), Justus-Liebig-University, Giessen, Germany.
Stud Health Technol Inform. 2018;253:40-44.
Metadata management is an important task in medical informatics and highly affects the gain out of existing health information data. Data Warehouse solutions like Informatics for Integrating Biology and the Bedside (i2b2) are common tools for identifying patient cohorts and analyzing collected clinical data while respecting patient privacy. The Resource Description Framework (RDF) is designed for highly interoperable ontology representation in various formats, facilitating ontology and metadata management. Our approach is to combine i2b2's and RDF's benefits by importing the easy-to-edit RDF ontology into the extensive-research-enabling i2b2 software. We do so by using a SPARQL Protocol and RDF Query Language (SPARQL) interface, that enables RDF data queries, and developing a java program, which then generates i2b2-specific SQL insert statements. To demonstrate our solution's feasibility, we transcribe our lung disease specific ontology to RDF and import it into our i2b2 data warehouse.
元数据管理是医学信息学中的一项重要任务,对从现有健康信息数据中获取收益有很大影响。像整合生物学与床边信息学(i2b2)这样的数据仓库解决方案是识别患者队列和分析收集到的临床数据同时尊重患者隐私的常用工具。资源描述框架(RDF)旨在以各种格式进行高度可互操作的本体表示,便于本体和元数据管理。我们的方法是通过将易于编辑的RDF本体导入支持广泛研究的i2b2软件,来结合i2b2和RDF的优势。我们通过使用一个支持RDF数据查询的SPARQL协议和RDF查询语言(SPARQL)接口,并开发一个Java程序来实现,该程序随后生成特定于i2b2的SQL插入语句。为了证明我们解决方案的可行性,我们将特定于肺病的本体转录为RDF并将其导入我们的i2b2数据仓库。