Johns Hopkins University, Baltimore, MD.
Janeiro Digital, Boston, MA.
AMIA Annu Symp Proc. 2021 Jan 25;2020:1140-1149. eCollection 2020.
This study developed and evaluated a JSON-LD 1.1 approach to automate the Resource Description Framework (RDF) serialization and deserialization of Fast Healthcare Interoperability Resources (FHIR) data, in preparation for updating the FHIR RDF standard. We first demonstrated that this JSON-LD 1.1 approach can produce the same output as the current FHIR RDF standard. We then used it to test, document and validate several proposed changes to the FHIR RDF specification, to address usability issues that were uncovered during trial use. This JSON-LD 1.1 approach was found to be effective and more declarative than the existing custom-code-based approach, in converting FHIR data from JSON to RDF and vice versa. This approach should enable future FHIR RDF servers to be implemented and maintained more easily.
本研究开发并评估了一种 JSON-LD 1.1 方法，以实现快速医疗互操作性资源 (FHIR) 数据的资源描述框架 (RDF) 序列化和反序列化的自动化，为更新 FHIR RDF 标准做准备。我们首先证明了这种 JSON-LD 1.1 方法可以产生与当前 FHIR RDF 标准相同的输出。然后，我们使用它来测试、记录和验证对 FHIR RDF 规范的几项提议变更，以解决在试用过程中发现的可用性问题。与现有的基于自定义代码的方法相比，这种 JSON-LD 1.1 方法在将 FHIR 数据从 JSON 转换为 RDF 或反之方面更有效、更具声明性。这种方法应该能够使未来的 FHIR RDF 服务器更容易实现和维护。
