Towards an open online repository of P. polycephalum networks and their corresponding graph representations

Dirnberger, Michael; Kehl, Tim; Mehlhorn, Tim; Mehlhorn, Kurt; Neumann, Adrian

doi:10.4108/eai.3-12-2015.2262469

Cited by 1 publication

(1 citation statement)

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“…A small repository is very flexible and can adapt and evolve more easily based on community feedback. In this form the idea of the SMGR was first introduced at PhysNet 2015 and was well received with individuals signaling their willingness to contribute data [11]. We strongly believe that a tight integration with the research community, is key to the future success of the SMGR.…”

Section: Repository Conceptmentioning

confidence: 99%

Introducing the slime mold graph repository

Dirnberger¹,

Mehlhorn²,

Mehlhorn³

2017

J. Phys. D: Appl. Phys.

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We introduce the Slime Mold Graph Repository, a novel data collection promoting the visibility, accessibility and reuse of experimental data revolving around network-forming slime molds. By making data instantly available for researchers across multiple disciplines, the SMGR promotes novel research as well as the reproduction of original results. While SMGR data may take various forms, we stress the importance of graph representations of slime mold networks due to their ease of handling and their large potential for reuse. Data added to the SMGR stands to gain impact beyond initial publications or even beyond its domain of origin. We initiate the SMGR with the comprehensive KIST Europe data set focused on the slime mold Physarum polycephalum. It contains sequences of images documenting growth and network formation of the organism under constant conditions. Suitable image sequences depicting the typical P. polycephalum network structures are used to compute sequences of graphs faithfully capturing them. Given such sequences, node identities are computed, tracking the development of nodes over time. The entire data set is well-documented, self-contained and ready for inspection via the SMGR at http://smgr.mpi-inf.mpg.de.

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Section: Repository Conceptmentioning

confidence: 99%