A Collaborative Informatics Infrastructure for Multi-Scale Science

Myers, James D.; Allison, Thomas C.; Bittner, Sandra; Didier, B.T.; Frenklach, Michael; Green, William; Ho, Yen-Ling; Hewson, John C.; Koegler, Wendy S.; Lansing, Carina; Leahy, David J.; Lee, Michael; McCoy, Renata; Minkoff, Michael; Nijsure, Sandeep; Laszewski, Gregor von; Montoya, David; Oluwole, Luwi; Pancerella, Carmen M.; Pinzón, Reinhardt; Pitz, William J.; Rahn, Larry A.; Ruščić, Branko; Schuchardt, Karen; Stephan, Eric G.; Wagner, Al; Windus, Theresa L.; Yang, Chung‐Chun

doi:10.1007/s10586-005-4092-4

Cited by 30 publications

(19 citation statements)

References 12 publications

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“…The Collaboratory for Multi-scale Chemical Science (CMCS) project is a data-oriented informatics toolkit for collaboration and data management for multi-scale chemistry (Myers et al, 2005). CMCS collects pedigree information about individual data objects by defining input and output data and capturing "pedigree chains" describing the processing that the data has undergone (http://cmcs.org).…”

Section: Discussionmentioning

confidence: 99%

Provenance in neuroimaging

et al. 2008

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Provenance, the description of the history of a set of data, has grown more important with the proliferation of research consortia-related efforts in neuroimaging. Knowledge about the origin and history of an image is crucial for establishing data and results quality; detailed information about how it was processed, including the specific software routines and operating systems that were used, is necessary for proper interpretation, high fidelity replication and re-use. We have drafted a mechanism for describing provenance in a simple and easy to use environment, alleviating the burden of documentation from the user while still providing a rich description of an image's provenance. This combination of ease of use and highly descriptive metadata should greatly facilitate the collection of provenance and subsequent sharing of data.

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Section: Discussionmentioning

confidence: 99%

Provenance in neuroimaging

et al. 2008

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“…Some of these ideas are also demonstrated in the World Wide Molecular Matrix [34] and the Collaboratory for Multiscale Chemical Science (CMCS) [35]. …”

Section: A Combechem/ebankmentioning

confidence: 99%

The Semantic Grid: Past, Present, and Future

2005

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“…This is due in part to increased access to high-performance Like other recent provenance research efforts [19][20][21], our research focuses on developing mechanisms for representing, collecting, storing, and disseminating provenance information on scientific data products. Our goal is to be able to work with any workflow execution environment.…”

Section: Introductionmentioning

confidence: 99%

Applying content management to automated provenance capture

Schuchardt

Gibson

Stephan

et al. 2007

Concurrency and Computation

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SUMMARYWorkflows and data pipelines are becoming increasingly valuable to computational and experimental sciences. These automated systems are capable of generating significantly more data within the same amount of time compared to their manual counterparts. Automatically capturing and recording data provenance and annotation as part of these workflows are critical for data management, verification, and dissemination. We have been prototyping a workflow provenance system, targeted at biological workflows, that extends our content management technologies and other open source tools. We applied this prototype to the provenance challenge to demonstrate an end-to-end system that supports dynamic provenance capture, persistent content management, and dynamic searches of both provenance and metadata. We describe our prototype, which extends the Kepler system for the execution environment, the Scientific Annotation Middleware (SAM) content management software for data services, and an existing HTTPbased query protocol. Our implementation offers several unique capabilities, and through the use of standards, is able to provide access to the provenance record with a variety of commonly available client tools.

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A Collaborative Informatics Infrastructure for Multi-Scale Science

Cited by 30 publications

References 12 publications

Provenance in neuroimaging

Provenance in neuroimaging

The Semantic Grid: Past, Present, and Future

Applying content management to automated provenance capture

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