Ontology-based data integration between clinical and research systems.

Ontology-based data integration between clinical and research systems.
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DOI:
10.1371/journal.pone.0116656
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发表时间:
2015
期刊:
影响因子:
3.7
通讯作者:
Ganslandt T
Ganslandt T
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Mate S;Köpcke F;Toddenroth D;Martin M;Prokosch HU;Bürkle T;Ganslandt T

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来自电子病历的数据包含许多结构化但未编码的元素,这些元素与标准术语没有关联。最近,将这些数据用于二级研究目的变得越来越重要。然而,识别相关数据元素和创建用于提取、转换和加载(ETL)的数据库作业是具有挑战性的:使用数据仓库等当前方法,无法有效地维护和重用语义复杂的数据提取和转换例程。我们提出了一种本体支持的方法,通过使用抽象来克服这一挑战:我们使用本体来组织和描述源系统和目标系统的医学概念,而不是在数据库级别定义ETL过程。我们没有使用唯一的、专门开发的SQL语句或ETL作业,而是在本体中定义声明性转换规则,并说明如何使用这些构造自动生成SQL代码来执行所需的ETL过程。这证明了一个合适的抽象层次不仅可以帮助临床数据的解释,而且还可以促进解锁方法的重用。
Data from the electronic medical record comprise numerous structured but uncoded ele-ments, which are not linked to standard terminologies. Reuse of such data for secondary research purposes has gained in importance recently. However, the identification of rele-vant data elements and the creation of database jobs for extraction, transformation and loading (ETL) are challenging: With current methods such as data warehousing, it is not feasible to efficiently maintain and reuse semantically complex data extraction and trans-formation routines. We present an ontology-supported approach to overcome this challenge by making use of abstraction: Instead of defining ETL procedures at the database level, we use ontologies to organize and describe the medical concepts of both the source system and the target system. Instead of using unique, specifically developed SQL statements or ETL jobs, we define declarative transformation rules within ontologies and illustrate how these constructs can then be used to automatically generate SQL code to perform the desired ETL procedures. This demonstrates how a suitable level of abstraction may not only aid the interpretation of clinical data, but can also foster the reutilization of methods for un-locking it.
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