FAIRClinical: FAIR-ification of Supplementary Data to Support Clinical Research

该项目旨在提高所有补充数据文件的公正性，并显著提高非结构化临床病例报告表格(CRF)的重复使用。补充数据通常附加到科学出版物上，或者直接在生物医学图书馆(如PMC)中，或通过通用的沉积平台，如Zenodo。文件类型和格式是高度不同的(例如，PDF、XLS、CSV、GIF等)。CRF收集临床研究和试验中的患者数据，并代表临床研究文献和非结构化临床研究补充数据中信息丰富的子集。我们建议通过提供更多标准化内容来具体丰富所有补充数据的内容，从而丰富其互操作性、可查找性和可重用性。设想的标准化将根据数据集管理目录中常见的四个维度来执行：1)管理元数据(例如，作者姓名、从属关系、许可模式)，2)描述性元数据(例如，疾病、基因或基因产品、人口大小、实验环境)，3)结构元数据(例如，文本内容、图像)，以及最后，4)对其他数据沉积目录的交叉引用(例如，URL、ID)。关于描述性元数据层，它可能会因生命和健康科学领域的不同而显著不同，我们建议探索临床信息的语义丰富。我们将提供涵盖所有PMC内容的补充数据文件的广泛公平化，并具体努力将CRF构建为类似电子健康记录(EHR)的数据集。我们建议处理CRF以提取使用标准值集(例如ICD-10、LOINC)填充参考标准(例如OMOP、FHIR)所需的临床概念。预期得到的数据集将显示与EHR内容非常相似的属性(例如，回忆、干预、诊断、处方)。与受特定法规约束的真实电子健康记录内容不同，这一独特的数据集将不受限制地访问，并可能支持广泛的健康和生命科学研究项目。新创建的NEAR EHR数据集合将在Zenodo上提供，而SIBiLS，即SIB文献服务，将用于提供对补充数据文件的访问，其方式与它已经提供对MEDLINE和PMC文章的访问相同。此外，这里开发的方法/管道对于构建非结构化CRF和医院设置中的其他非结构化临床文本是有用的工具箱。

The project aims to enhance the FAIR-ness of all supplementary data files and significantly improve the reuse of unstructured clinical case report forms (CRFs). Supplementary data are commonly attached to a scientific publication, either directly in biomedical libraries such as PMC, or via generalist deposition platforms such as Zenodo. The file types and formats are highly heterogeneous (e.g., PDF, XLS, CSV, GIF, etc.). CRFs collect the patient data in clinical research studies and trials, and represent an information-rich subset of clinical research literature and unstructured clinical study supplementary data. We propose to specifically enrich the contents - and therefore the interoperability, findability and reusability - of all supplementary data by delivering more normalised contents.The envisaged normalisation will be performed according to four dimensions, which are common in dataset management catalogues: 1) administrative metadata (e.g., author names, affiliations, licensing models), 2) descriptive metadata (e.g., diseases, gene or gene products, size of populations, experimental settings), 3) structural metadata (e.g., textual contents, images) and finally, 4) cross-references to other data deposition catalogues (e.g., URL, PID). Regarding the descriptive metadata layer, which may significantly vary depending on specialised life and health science areas, we propose to explore the semantic enrichment of clinical information. We will provide broad FAIR-ification of supplementary data files, covering all PMC contents, combined with a specific effort to structure CRFs into an Electronic Health Records (EHR)-like dataset.We propose to process CRFs to extract clinical concepts required to populate reference standards (e.g., OMOP, FHIR) using standard value sets (e.g., ICD-10, LOINC). The resulting dataset is expected to exhibit properties very similar to EHR contents (e.g., Anamnesis, Intervention, Diagnosis, Prescription). Unlike real EHR contents, which are subject to specific regulations, this unique dataset will be of unrestricted access and likely to support a broad range of health and life science research projects. The newly created collection of near EHR data will be made available on Zenodo, while the SIBiLS, the SIB Literature Services, will be used to provide access to the supplementary data files the same way it is already providing access to MEDLINE and PMC articles. In addition, the methods/pipelines developed here are useful as a toolbox to structure unstructured CRFs and other unstructured clinical text in hospital setups.