Cunningham James A, Van Speybroeck Michel, Kalra Dipak, Verbeeck Rudi
Health e-Research Centre, The University of Manchester, Manchester, UK.
Janssen Pharmaceutica, Beerse, Belgium.
AMIA Annu Symp Proc. 2017 Feb 10;2016:451-459. eCollection 2016.
Medical data is routinely collected, stored and recorded across different institutions and in a range of different formats. Semantic harmonization is the process of collating this data into a singular consistent logical view, with many approaches to harmonizing both possible and valid. The broad scope of possibilities for undertaking semantic harmonization do lead however to the development of bespoke and ad-hoc systems; this is particularly the case when it comes to cohort data, the format of which is often specific to a cohort's area of focus. Guided by work we have undertaken in developing the 'EMIF Knowledge Object Library', a semantic harmonization framework underpinning the collation of pan-European Alzheimer's cohort data, we have developed a set of nine generic guiding principles for developing semantic harmonization frameworks, the application of which will establish a solid base for constructing similar frameworks.
医学数据通常在不同机构以多种不同格式进行收集、存储和记录。语义协调是将这些数据整理成单一一致的逻辑视图的过程,有许多协调方法都是可行且有效的。然而,进行语义协调的广泛可能性确实导致了定制化和临时系统的开发;在处理队列数据时尤其如此,队列数据的格式通常特定于队列的关注领域。在我们开发“欧洲医学信息框架知识对象库”(这是一个支持泛欧洲阿尔茨海默病队列数据整理的语义协调框架)的工作指导下,我们制定了一套九条通用指导原则来开发语义协调框架,这些原则的应用将为构建类似框架奠定坚实基础。