In the field of neuroscience, a considerable number of commercial data acquisition and processing solutions rely on proprietary formats for data storage. This often leads to data being locked up in formats that are only accessible by using the original software, which may lead to interoperability problems. In fact, even the loss of data access is possible if the software becomes unsupported, changed, or otherwise unavailable. To ensure FAIR data management, strategies should be established to enable long-term, independent, and unified access to data in proprietary formats. In this work, we demonstrate PyDapsys, a solution to gain open access to data that was acquired using the proprietary recording system DAPSYS. PyDapsys enables us to open the recorded files directly in Python and saves them as NIX files, commonly used for open research in the electrophysiology domain. Thus, PyDapsys secures efficient and open access to existing and prospective data. The manuscript demonstrates the complete process of reverse engineering a proprietary electrophysiological format on the example of microneurography data collected for studies on pain and itch signaling in peripheral neural fibers.

中文翻译：

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PyDapsys：一个开源库，用于访问用 DAPSYS 记录的电生理学数据

在神经科学领域，相当多的商业数据采集和处理解决方案依赖于专有格式进行数据存储。这通常会导致数据被锁定为只能通过使用原始软件访问的格式，这可能会导致互操作性问题。事实上，如果软件不受支持、发生更改或以其他方式不可用，甚至可能会丢失数据访问权限。为了确保公平的数据管理，应制定策略以实现对专有格式数据的长期、独立和统一访问。在这项工作中，我们演示了 PyDapsys，这是一种开放访问使用专有记录系统 DAPSYS 获取的数据的解决方案。PyDapsys 使我们能够直接在 Python 中打开记录的文件并将其保存为 NIX 文件，通常用于电生理学领域的开放研究。因此，PyDapsys 可确保对现有和未来数据的高效和开放访问。该手稿展示了对一种专有的电生理学格式进行逆向工程的完整过程，以收集用于研究周围神经纤维中的疼痛和瘙痒信号的微神经造影数据为例。