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The Trident Scientific Workflow Workbench

, , , , , and . IEEE International Conference on eScience (eScience), page 317--318. IEEE, (2008)Demo CORE A.
DOI: 10.1109/eScience.2008.126

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Reliable Management of Community Data Pipelines using Scientific Workflows, , , , and . MSR-TR-2009-125. Microsoft Research, (September 2009)Analysis of approaches for supporting the Open Provenance Model: A case study of the Trident workflow workbench, and . Future Generation Computer Systems (FGCS), 27 (6): 790--796 (2011)IF 2.43, CORE A.Predictive Analytics with Microsoft Azure Machine Learning, , and . Apress, New York, 2 edition, (2015)Building the Trident Scientific Workflow Workbench for Data Management in the Cloud, , , , and . Conference on Advanced Engineering Computing and Applications in Sciences (ADVCOMP), page 41--50. IEEE, (October 2009)GrayWulf: Scalable Software Architecture for Data Intensive Computing, , , , , , , , , and . MSR-TR-2008-186. Microsoft Research, (September 2008)Pan-STARRS: Learning to Ride the Data Tsunami, , , , , , , , , and 1 other author(s). Microsoft Research eScience Workshop, Microsoft, (December 2008)Talk.Automatic Provenance Recording for Scientific Data using Trident, , and . American Geophysical Union (AGU) Fall Meeting, AGU, (2008)Poster.Provenance for Scientific Workflows: Towards Reproducible Research, , , , , and . Data Engineering Bulletin (DEB), 33 (3): 50--59 (September 2010)The Open Provenance Model (v1.01), , , , , , , , , and 8 other author(s). 16148. Intelligence, Agents, Multimedia Group, University of Southampton, (July 2008)Predictive Analytics with Microsoft Azure Machine Learning - Build and Deploy Actionalbe Solutions in Minutes, Second Edition., , and . Apress, (2015)