ODML-Tables 作为微神经生理学中的元数据标准。

odML-Tables as a Metadata Standard in Microneurography.

机构信息

Research Group Neuroscience, IZKF, Department of Physiology, RWTH Aachen University, Aachen, Germany.

School of Physiology, Pharmacology and Neuroscience Bristol Anaesthesia, Critical Care and Pain Research, University of Bristol, UK.

出版信息

Stud Health Technol Inform. 2023 Sep 12;307:3-11. doi: 10.3233/SHTI230687.

DOI:10.3233/SHTI230687

PMID:37697832

Abstract

Metadata is essential for handling medical data according to FAIR principles. Standards are well-established for many types of electrophysiological methods but are still lacking for microneurographic recordings of peripheral sensory nerve fibers in humans. Developing a new concept to enhance laboratory workflows is a complex process. We propose a standard for structuring and storing microneurography metadata based on odML and odML-tables. Further, we present an extension to the odML-tables GUI that enables user-friendly search functionality of the database. With our open-source repository, we encourage other microneurography labs to incorporate odML-based metadata into their experimental routines.

摘要

元数据对于按照 FAIR 原则处理医学数据至关重要。许多类型的电生理方法都有成熟的标准，但对于人类周围感觉神经纤维的微神经记录仍然缺乏标准。开发一个增强实验室工作流程的新概念是一个复杂的过程。我们提出了一种基于 odML 和 odML-tables 的微神经记录元数据结构和存储标准。此外，我们还对 odML-tables GUI 进行了扩展，使其具有用户友好的数据库搜索功能。通过我们的开源存储库，我们鼓励其他微神经记录实验室将基于 odML 的元数据纳入他们的实验常规中。