Evidence map›Paper›PMID 24971059›Full record

ArticleFrontiers in neuroinformatics2014

NeuronDepot: keeping your colleagues in sync by combining modern cloud storage services, the local file system, and simple web applications.

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 read
In one paragraph

Article in Frontiers in neuroinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Philipp L RautenbergDepartment of Biology II, G-Node, Ludwig-Maximilians-Universität München Planegg-Martinsried, Germany ; Department for Innovations, Max Planck Digital Library München, Germany.
Ajayrama KumaraswamyDepartment of Biology II, G-Node, Ludwig-Maximilians-Universität München Planegg-Martinsried, Germany.
Alvaro Tejero-CanteroMRC ANU, Department of Pharmacology, University of Oxford Oxford, UK.
Christoph DoblanderDepartment of Informatics, Technische Universität München München, Germany.
Mohammad R NorouzianDepartment of Informatics, Technische Universität München München, Germany.
Kazuki KaiDepartment of Earth System Science, Fukuoka University Fukuoka, Japan.
Hans-Arno JacobsenDepartment of Informatics, Technische Universität München München, Germany.
Hiroyuki AiDepartment of Earth System Science, Fukuoka University Fukuoka, Japan.
Thomas WachtlerDepartment of Biology II, G-Node, Ludwig-Maximilians-Universität München Planegg-Martinsried, Germany.
Hidetoshi IkenoSchool of Human Science and Environment, University of Hyogo Hyogo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

cloud servicesdata managementelectrophysiologyimagingmorphologyneuroinformaticsresearch data management

Identifiers

PMID24971059
PMCPMC4053686

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.