LONI Pipeline: Difference between revisions

Content deleted Content added

Inline

Revision as of 18:22, 23 June 2012

The LONI Pipeline is a distributed system for constructing, validating, executing and disseminating scientific workflows^[1]^[2] on grid computing architectures. A major difference between this and other workflow processing environments is that the LONI Pipeline does not require new tools and services to include, or be built against, the core Pipeline libraries. The Pipeline environment references all data, services and tools as external objects. This allows the Pipeline to run as a light-weight middleware, but at the same time, restricts the scope of its applications. For example, the Pipeline does not provide a set of internal core libraries, filters and processes for rudimentary image processing (e.g., image addition). All tools necessary to complete an analysis protocol must first be built as external stand-alone applications or services, whose interface methods are then described in the Pipeline XML language. Users may choose to share these XML module descriptions to avoid duplicate work. Typical pipeline server installations include a suite of core resources that are available to all users with access to the specific server, however, different servers will have different suites of default module and module-group (pipeline) definitions. Version 5 of the LONI Pipeline^[3] provides a mechanism for integrating heterogeneous and incongruous data including images, clinical charts and demographic meta-data.

References

^ Rex, D. E., Ma, J.Q., and Toga, A.W. (2003). "The LONI Pipeline Processing Environment." Neuroimage, 19(3), 1033-48.
^ Rex, D. E., Shattuck, D. W., Woods, R. P., Narr, K. L., Luders, E., Rehm, K., Stolzner, S. E., Rottenberg, D. E., and Toga, A. W. (2004). "A meta-algorithm for brain extraction in MRI." NeuroImage, 23(2), 625–637
^ Dinov ID, Lozev K, Petrosyan P, Liu Z, Eggert P, Pierce, J, Zamanyan, A, Chakrapani, S, Van Horn, JD, Parker, DS, Magsipoc, R, Leung, K, Gutman, B, Woods, RP, Toga, AW. (2010). "Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline." PLoS ONE 5(9): e13070. doi:10.1371/journal.pone.0013070.

External links

LONI Pipeline website

[Rex03-1] Rex, D. E., Ma, J.Q., and Toga, A.W. (2003). "The LONI Pipeline Processing Environment." Neuroimage, 19(3), 1033-48.

[Rex04-2] Rex, D. E., Shattuck, D. W., Woods, R. P., Narr, K. L., Luders, E., Rehm, K., Stolzner, S. E., Rottenberg, D. E., and Toga, A. W. (2004). "A meta-algorithm for brain extraction in MRI." NeuroImage, 23(2), 625–637

[Dinov_PLoSONE_2010-3] Dinov ID, Lozev K, Petrosyan P, Liu Z, Eggert P, Pierce, J, Zamanyan, A, Chakrapani, S, Van Horn, JD, Parker, DS, Magsipoc, R, Leung, K, Gutman, B, Woods, RP, Toga, AW. (2010). "Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline." PLoS ONE 5(9): e13070. doi:10.1371/journal.pone.0013070.

[1]

[2]

[3]

@@ Line 1: / Line 1: @@
 [[Image:LONI Pipeline.png|thumb|right|The LONI Pipeline]]
-The LONI Pipeline is a distributed system for constructing, validating, executing and disseminating scientific [[workflows]]<ref name="Rex03">Rex, D. E., Ma, J.Q., and Toga, A.W. (2003). "The LONI Pipeline Processing Environment." Neuroimage, 19(3), 1033-48.</ref><ref name="Rex04">Rex, D. E., Shattuck, D. W., Woods, R. P., Narr, K. L., Luders, E., Rehm, K., Stolzner, S. E., Rottenberg, D. E., and Toga, A. W. (2004). "A meta-algorithm for brain extraction in MRI." NeuroImage, 23(2), 625–637</ref> on [[grid computing]] architectures. A major difference between this and [[Workflow technology | other workflow processing environments]] is that the LONI Pipeline does not require new tools and services to include, or be built against, the core Pipeline libraries. The Pipeline environment references all data, services and tools as external objects. This allows the Pipeline to run as a light-weight middleware, but at the same time, restricts the scope of its applications. For example, the Pipeline does not provide a set of internal core libraries, filters and processes for rudimentary image processing (e.g., image addition). All tools necessary to complete an analysis protocol must first be built as external stand-alone applications or services, whose interface methods are then described in the Pipeline XML language. Users may choose to share these XML module descriptions to avoid duplicate work. Typical pipeline server installations include a suite of core resources that are available to all users with access to the specific server, however, different servers will have different suites of default module and module-group (pipeline) definitions. Version 5 of the LONI Pipeline<ref name="Dinov_PLoSONE_2010">Dinov ID, Lozev K,  Petrosyan P,  Liu Z,  Eggert P, Pierce, J, Zamanyan, A, Chakrapani, S, Van Horn, JD, Parker, DS, Magsipoc, R, Leung, K, Gutman, B, Woods, RP, Toga, AW. (2010). "Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline." PLoS ONE 5(9): e13070. doi:10.1371/journal.pone.0013070.</ref> provides a mechanism for integrating heterogeneous and incongruous data including images, clinical charts and demographic meta-data.
+The LONI Pipeline is a distributed system for constructing, validating, executing and disseminating scientific [[workflows]]<ref name="Rex03">Rex, D. E., Ma, J.Q., and Toga, A.W. (2003). "The LONI Pipeline Processing Environment." Neuroimage, 19(3), 1033-48.</ref><ref name="Rex04">Rex, D. E., Shattuck, D. W., Woods, R. P., Narr, K. L., Luders, E., Rehm, K., Stolzner, S. E., Rottenberg, D. E., and Toga, A. W. (2004). "A meta-algorithm for brain extraction in MRI." NeuroImage, 23(2), 625–637</ref> on [[grid computing]] architectures. A major difference between this and [[Workflow technology | other workflow processing environments]] is that the LONI Pipeline does not require new tools and services to include, or be built against, the core Pipeline libraries. The Pipeline environment references all data, services and tools as external objects. This allows the Pipeline to run as a light-weight middleware, but at the same time, restricts the scope of its applications. For example, the Pipeline does not provide a set of internal core libraries, filters and processes for rudimentary image processing (e.g., image addition). All tools necessary to complete an analysis protocol must first be built as external stand-alone applications or services, whose interface methods are then described in the Pipeline XML language. Users may choose to share these XML module descriptions to avoid duplicate work. Typical pipeline server installations include a suite of core resources that are available to all users with access to the specific server, however, different servers will have different suites of default module and module-group (pipeline) definitions. Version 5 of the LONI Pipeline<ref name="Dinov_PLoSONE_2010">Dinov ID, Lozev K,  Petrosyan P,  Liu Z,  Eggert P, Pierce, J, Zamanyan, A, Chakrapani, S, Van Horn, JD, Parker, DS, Magsipoc, R, Leung, K, Gutman, B, Woods, RP, Toga, AW. (2010). "Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline." PLoS ONE 5(9): e13070. {{doi|10.1371/journal.pone.0013070}}.</ref> provides a mechanism for integrating heterogeneous and incongruous data including images, clinical charts and demographic meta-data.
 == See also ==