This title appears in the Scientific Report :
2017
Designing collaborative workflows for reproducible data analysis in electrophysiology based on the Elephant analysis framework
Designing collaborative workflows for reproducible data analysis in electrophysiology based on the Elephant analysis framework
In the previous decade the degree of complexity in analyzing massively parallel, heterogeneous data from electrophysiological experiments and network simulations has reached levels where novel tools that form workflows for managing data and metadata acquisition, pre-processing, and analysis in a rep...
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Personal Name(s): | Denker, Michael (Corresponding author) |
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Yegenoglu, Alper / Grün, Sonja | |
Contributing Institute: |
Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 Computational and Systems Neuroscience; INM-6 |
Imprint: |
2017
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Conference: | Neuroscience 2017, Makuhari (Japan), 2017-07-20 - 2017-07-23 |
Document Type: |
Abstract |
Research Program: |
Supercomputing and Modelling for the Human Brain Human Brain Project Specific Grant Agreement 1 Theory, modelling and simulation |
Publikationsportal JuSER |
In the previous decade the degree of complexity in analyzing massively parallel, heterogeneous data from electrophysiological experiments and network simulations has reached levels where novel tools that form workflows for managing data and metadata acquisition, pre-processing, and analysis in a reproducible fashion are in high demand [1]. The Human Brain Project (HBP) aims at creating and operating a scientific research infrastructure for the neurosciences to address these needs for such integrative software environments.Here, by means of a collaborative case study, we outline how the HBP framework supports analysis workflows by combining various software components hosted on a common platform. 3 emerging open-source software tools represent the scaffold from which the analysis pipelines are built: (i) data of different origins are represented in a standard form using the Neo framework [2], (ii) complex metadata accumulating in the electrophysiological experiment [3] are managed using the open metadata markup language (odML) [4], and (iii) analysis is performed using the Electrophysiology Analysis Toolkit (Elephant, http://neuralensemble.org/elephant/) as a recent community-centered analysis framework for multi-scale activity data. As such, Elephant represents a modular software component that provides generic library functions to perform standard and advanced analysis processes. We outline how the integration of the workflow into the HBP Collaboratory infrastructure (http://www.collab.humanbrainproject.eu) facilitates interdisciplinary, collaborative work including provenance tracking, and provides access to high-performance computing for advanced analysis approaches. Conceptually, the presented work follows [5].References:[1] Badia, R. et al. (2015) INCF Program on Standards for data sharing: new perspectives on workflows and data management for the analysis of electrophysiological data. Techn. Report, https://www.incf.org/about-us/history/incf-scientific-workshops[2] Garcia, S. et al. (2014) Neo: an object model for handling electrophysiology data in multiple formats. Front Neuroinf 8, 10.[3] Zehl, L. et al. (2016) Front Neuroinf, 10, 26.[4] Grewe, J. et al. (2011) Front Neuroinf 5, 16.[5] Denker, M., Gruen, S. (2016). Designing Workflows for the Reproducible Analysis of Electrophysiological Data. In Brain-Inspired Computing, Amunts, K. et al., eds. (Cham: Springer International Publishing), pp. 58-72. 研究助成:Research funds : Helmholtz Portfolio Theme Supercomputing and Modeling for the Human Brain (SMHB), EU grant 720270 (Human Brain Project, HBP) |