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. 2012 Nov 27:13:315.
doi: 10.1186/1471-2105-13-315.

CloudMan as a platform for tool, data, and analysis distribution

Enis Afgan  1 , Brad Chapman, James Taylor
Affiliations

CloudMan as a platform for tool, data, and analysis distribution

Enis Afgan et al. BMC Bioinformatics. .

Abstract

Background: Cloud computing provides an infrastructure that facilitates large scale computational analysis in a scalable, democratized fashion, However, in this context it is difficult to ensure sharing of an analysis environment and associated data in a scalable and precisely reproducible way.

Results: CloudMan (usecloudman.org) enables individual researchers to easily deploy, customize, and share their entire cloud analysis environment, including data, tools, and configurations.

Conclusions: With the enabled customization and sharing of instances, CloudMan can be used as a platform for collaboration. The presented solution improves accessibility of cloud resources, tools, and data to the level of an individual researcher and contributes toward reproducibility and transparency of research solutions.

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Figures

Figure 1
Figure 1
A conceptual representation of CloudMan’s architectural components that facilitate customization and sharing of instances. Each instance is self-contained by keeping track of the configuration components that make up the deployment. As a result, it is possible to create custom versions of the default set of tools or indices. For example, instance A is using the default configuration (EBS snapshots colored in blue) while instance B has been customized (colored in yellow and orange). Once customizations are created, they can be shared with specific users (denoted with ‘S’) or made public (denoted with ‘P’). Instances are shared as point in time data and configuration. In the shown example, instance B has been shared at two time points. Any derived instances (instance C) will use the shared instance configuration settings upon startup. Each instance has its own user data; derived instances use the shared instance’s data and build on top of it.
Figure 2
Figure 2
Web interface used to share an instance and later create a derived instance. (A) A user can chose to make an instance public or share it with specific user or group of users. (B) Once shared, the time point share is assigned a share ID string. This string is shared with users, who simply (C) provide the share ID string at the time of new cluster instantiation to create a derived cluster.
See this image and copyright information in PMC

References

    1. Afgan E, Baker D, Coraor N, Chapman B, Nekrutenko A, Taylor J. Galaxy CloudMan: delivering cloud compute clusters. BMC Bioinformatics. 2010;11(12):S4. doi: 10.1186/1471-2105-11-S12-S4. - DOI - PMC - PubMed
    1. Afgan E, Baker D, Coraor N, Goto H, Makova K, Nekrutenko A, Taylor J. Harnessing cloud-computing for biomedical research with Galaxy Cloud. Nat Biotechnol. 2011;29(11):972–974. doi: 10.1038/nbt.2028. - DOI - PMC - PubMed
    1. Cloud Biolinux. http://www.cloudbiolinux.com/
    1. Goecks J, Nekrutenko A, Taylor J. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 2010;11(8):R86. doi: 10.1186/gb-2010-11-8-r86. - DOI - PMC - PubMed
    1. Afgan E, Goecks J, Baker D, Coraor N, Nekrutenko A, Taylor J. In: Guide to e-science: next generation scientific research and discovery. Yang K, editor. London: Springer; 2011. Galaxy - a gateway to tools in e-science; pp. 145–177.

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