% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@INPROCEEDINGS{Yegenoglu:850028,
author = {Yegenoglu, Alper and Denker, Michael and Grün, Sonja},
title = {{C}ollaborative {HPC}-enabled workflows on the {HBP}
{C}ollaboratory using the {E}lephant framework},
reportid = {FZJ-2018-04114},
year = {2018},
abstract = {The degree of complexity in analyzing massively parallel,
heterogeneous data from electrophysiological experiments and
network simulations has reached levels where novel tools
forming workflows for managing data, metadata acquisition,
pre-processing, and analysis in a reproducible fashion are
in high demand. Moreover, this complexity calls for new
conceptual approaches in organizing scientific work. The
nature of these new, highly manifold projects requires work
to be performed in larger, multi-disciplinary
collaborations. The collaborators that need to interact
closely require the supported from powerful computing
resources, especially when dealing with large and diverse
data sets.The Human Brain Project (HBP,
http://humanbrainproject.eu/) aims at creating and operating
a scientific research infrastructure for the neurosciences
to address such needs for integrative software environments.
At its core, the HBP features the Collaboratory
(http://www.collab.humanbrainproject.eu), a web-based
platform to jointly implement research projects. It enables
the ability to create so-called “Collabs” that consist
of a joint workspace and associated apps (see also poster by
van Papen et al). An app provides the functionality to
launch Jupyter notebooks, which is in particular interesting
for interactive data analysis. Powerful as this approach
appears on paper, it is unclear how these developments
translate into implementing complete analysis workflows in a
real-world collaborative analysis scenario. Here, we show
how diverse tools, from software development, general
science and software specific for neuroscience can be
successfully combined in a to form a collaborative analysis
workflow hosted on the HBP Collaboratory. Three emerging
open-source software tools from neuroscience represent the
tool basis which builds the analysis pipeline: (i) data of
different origins are represented in a standard form using
the Neo framework, (ii) complex metadata accumulated in
relation to an electrophysiological experiment are managed
using the open metadata markup language (odML) and (iii)
analysis is performed utilizing the Electrophysiology
Analysis Toolkit (Elephant,
http://neuralensemble.org/elephant/). The Elephant tool is a
recent community-centered analysis framework for the
analysis of multi-scale high-dimensional activity data.
Elephant is a modular software component that provides
generic library functions to perform standard and advanced
analysis. All these domain-specific tools are augmented by
generic tools, such as version control systems or workflow
management solutions, to form a blueprint for performing
interdisciplinary, collaborative work including access to
high-performance computing facilities for advanced, but
computational demanding analyses.},
month = {Jul},
date = {2018-07-02},
organization = {INM-ICS Retreat 2018, Juelich
(Germany), 2 Jul 2018 - 3 Jul 2018},
cin = {INM-6 / IAS-6 / INM-10},
cid = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)IAS-6-20130828 /
I:(DE-Juel1)INM-10-20170113},
pnm = {571 - Connectivity and Activity (POF3-571) / SMHB -
Supercomputing and Modelling for the Human Brain
(HGF-SMHB-2013-2017) / HBP SGA1 - Human Brain Project
Specific Grant Agreement 1 (720270) / HBP SGA2 - Human Brain
Project Specific Grant Agreement 2 (785907)},
pid = {G:(DE-HGF)POF3-571 / G:(DE-Juel1)HGF-SMHB-2013-2017 /
G:(EU-Grant)720270 / G:(EU-Grant)785907},
typ = {PUB:(DE-HGF)1},
url = {https://juser.fz-juelich.de/record/850028},
}