INCF Workshop Report: New Perspectives on Workflows and Data Management for the Analysis of Electrophysiological Data
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1
Jülich Research Centre and JARA, Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Germany
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2
INCF Secretariat/Karolinska Institutet, Sweden
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3
Ludwig-Maximilians-Universität München, Biology II, Germany
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4
CNRS UPR 3293, Unité de Neurosciences, Information et Complexité, Neuroinformatics group, France
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5
RWTH Aachen University, Theoretical Systems Neurobiology, Germany
Breakthroughs in recording technologies and analysis approaches have led to unprecedented levels of complexity in electrophysiological experiments. The ability to perform massively parallel recordings from hundreds of neurons in the brain paired with a strong interest in complex, natural stimulation and behavioral paradigms, results in a surge of intricately interwoven incoming data that require to be analyzed with sophisticated methods. These factors pose a challenge for researchers who, over the course of years, are confronted with planning of the analysis, organization of workflows in larger teams, programming of software, and bookkeeping of the results obtained by constantly evolving analysis methods.
The complexity of electrophysiological research has reached a level where a well-structured data analysis workflow has become a necessity. The INCF Program on Standards for Data Sharing supported the organization of a 2-day workshop to provide a discussion platform for researchers and developers who work on components that are instrumental in such workflows. The workshop focused on three major issues related to workflows in electrophysiology: (i) data structures and software libraries that enable interfacing of data from various sources and integration of methods for data manipulation and analysis, (ii) documentation and provenance tracking solutions to support reproducible analysis processes able to cope with the required levels of flexibility and data size, and (iii) workflow management systems that allow automatic and extensible processing of complex analysis workflows, in particular on high performance computers. In addition, experimental neuroscientists reported on workflow related needs from the user’s perspective.
In this presentation, we summarize the existing approaches for data structures/software libraries, documentation/provenance, workflow management systems, and supercomputing that were highlighted during the workshop, and discuss how these are related from the perspective of the workflow. We point out the challenges identified by the participants for workflows and data management in electrophysiology. Finally, we present the conclusions of the workshop which were formulated as a set of recommendations for the INCF how to improve the workflow/data management situation based on INCF’s activities within this domain.
Acknowledgements
This work is the outcome of a workshop sponsored by the International Neuroinformatics Coordinating Facility (INCF) on New perspectives on workflows and data management for the analysis of electrophysiological data. Supported by: SMHB, Human Brain Project (EU grant 604102), G-Node (BMBF Grant 01GQ1302), BrainScaleS (EU Grant 269912).
Keywords:
workflows,
Electrophysiology,
data management,
Reproducible Research,
workshop,
provenance,
meta data
Conference:
Neuroinformatics 2014, Leiden, Netherlands, 25 Aug - 27 Aug, 2014.
Presentation Type:
Poster, not to be considered for oral presentation
Topic:
Electrophysiology
Citation:
Denker
M,
Abrams
MB,
Wachtler
T,
Davison
AP and
Grün
S
(2014). INCF Workshop Report: New Perspectives on Workflows and Data Management for the Analysis of Electrophysiological Data.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2014.
doi: 10.3389/conf.fninf.2014.18.00021
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Received:
22 Apr 2014;
Published Online:
04 Jun 2014.
*
Correspondence:
Dr. Michael Denker, Jülich Research Centre and JARA, Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6), Jülich, 52425, Germany, m.denker@fz-juelich.de