Philipp L. Rautenberg, Ajayrama Kumaraswamy, Alvaro Tejero-Cantero, Christoph Doblander, Mohammad R. Norouzian, Kazuki Kai, Hans-Arno Jacobsen, Hiroyuki Ai, Thomas Wachtler, Hidetoshi Ikeno
Abstract
Neuroscience today deals with a "data deluge" derived from the availability of high-throughput sensors of brain structure and brain activity, and increased computational resources for detailed simulations with complex output. We report here (1) a novel approach to data sharing between collaborating scientists that brings together file system tools and cloud technologies, (2) a service implementing this approach, called NeuronDepot, and (3) an example application of the service to a complex use case in the neurosciences. The main drivers for our approach are to facilitate collaborations with a transparent, automated data flow that shields scientists from having to learn new tools or data structuring paradigms. Using NeuronDepot is simple: one-time data assignment from the originator and cloud based syncing-thus making experimental and modeling data available across the collaboration with minimum overhead. Since data sharing is cloud based, our approach opens up the possibility of using new software developments and hardware scalabitliy which are associated with elastic cloud computing. We provide an implementation that relies on existing synchronization services and is usable from all devices via a reactive web interface. We are motivating our solution by solving the practical problems of the GinJang project, a collaboration of three universities across eight time zones with a complex workflow encompassing data from electrophysiological recordings, imaging, morphological reconstructions, and simulations.
This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 December 2014.
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#7,474,859
of 22,852,911 outputs
Outputs from Frontiers in Neuroinformatics
#363
of 750 outputs
Outputs of similar age
#73,756
of 228,891 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#9
of 20 outputs
Altmetric has tracked 22,852,911 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 750 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one has gotten more attention than average, scoring higher than 50% of its peers.
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We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
