This title appears in the Scientific Report :
2023
Please use the identifier:
http://dx.doi.org/10.3389/fninf.2023.1250260 in citations.
Please use the identifier: http://dx.doi.org/10.34734/FZJ-2024-00414 in citations.
PyDapsys: an open-source library for accessing electrophysiology data recorded with DAPSYS
PyDapsys: an open-source library for accessing electrophysiology data recorded with DAPSYS
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 pr...
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Personal Name(s): | Konradi, Peter (Corresponding author) |
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Troglio, Alina / Pérez Garriga, Ariadna / Pérez Martín, Aarón / Röhrig, Rainer / Namer, Barbara / Kutafina, Ekaterina | |
Contributing Institute: |
Jülich Supercomputing Center; JSC |
Published in: | Frontiers in neuroinformatics, 17 (2023) S. 1250260 |
Imprint: |
Lausanne
Frontiers Research Foundation
2023
|
DOI: |
10.3389/fninf.2023.1250260 |
DOI: |
10.34734/FZJ-2024-00414 |
Document Type: |
Journal Article |
Research Program: |
SimLab Neuroscience Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups |
Link: |
OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.34734/FZJ-2024-00414 in citations.
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. |