Large-scale research integration is contingent on seamless access to data in standardized formats. Standards enable researchers to understand external experiment structures, pool results, and apply homogeneous preprocessing and analysis workflows. Particularly, they facilitate these features without the need for numerous potentially confounding compatibility add-ons. In small animal magnetic resonance imaging, an overwhelming proportion of data is acquired via the ParaVision software of the Bruker Corporation. The original data structure is predominantly transparent, but fundamentally incompatible with modern pipelines. Additionally, it sources metadata from free-field operator input, which diverges strongly between laboratories and researchers. In this article we present an open-source workflow which automatically converts and reposits data from the ParaVision structure into the widely supported and openly documented Brain Imaging Data Structure (BIDS). Complementing this workflow we also present operator guidelines for appropriate ParaVision data input, and a programmatic walk-through detailing how preexisting scans with uninterpretable metadata records can easily be made compliant after the acquisition.

大规模研究集成取决于对标准化格式数据的无缝访问。标准使研究人员能够了解外部实验结构，汇总结果，并应用同类的预处理和分析工作流程。尤其是，它们有助于实现这些功能，而无需大量潜在的混淆兼容性附件。在小动物磁共振成像中，绝大多数数据是通过布鲁克公司的ParaVision软件获取的。原始数据结构主要是透明的，但与现代管道根本不兼容。另外，它从自由场操作员的输入中获取元数据，这在实验室和研究人员之间存在很大差异。在本文中，我们提供了一个开源工作流，该工作流自动将ParaVision结构中的数据转换和存储为广泛支持并公开记录的Brain Imaging Data Structure（BIDS）。作为该工作流程的补充，我们还为适当的ParaVision数据输入提供了操作员指南，并提供了编程式演练，详细介绍了如何在采集后轻松使符合标准的现有扫描与无法解释的元数据记录相符。