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Nine Principles of Semantic Harmonization

机译:语义协调的九项原则

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摘要

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.
机译:跨不同机构以各种不同格式定期收集,存储和记录医学数据。语义协调是将这些数据整理为单一一致逻辑视图的过程,并采用许多方法来协调可能和有效的方法。但是,进行语义统一的广泛可能性确实导致了定制系统和临时系统的发展。当涉及同类群组数据时,尤其是这种情况,其格式通常特定于同类群组的关注领域。在开发“ EMIF知识对象库”(一种支持泛欧洲阿尔茨海默氏人群数据整理的语义协调框架)的工作的指导下,我们已经开发了一套九项通用指导原则,用于开发语义协调框架,这将为构建类似框架奠定坚实的基础。

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