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Supporting Large-Scale Science with Workflows Deana Pennington University of New Mexico Long-Term Ecological Research Network Office ITR: Science Environment.

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Presentation on theme: "Supporting Large-Scale Science with Workflows Deana Pennington University of New Mexico Long-Term Ecological Research Network Office ITR: Science Environment."— Presentation transcript:

1 Supporting Large-Scale Science with Workflows Deana Pennington University of New Mexico Long-Term Ecological Research Network Office ITR: Science Environment for Ecological Knowledge (SEEK) project CI-Team: Advancing CI-Based Science through Education, Training, and Mentoring of Science Communities WORKS ’07 June 25, 2007

2 Scientific Research Cycle Theory Hypothesis Experiment Results Inference Research Design Data flow Knowledge flow Design flow Knowledge flow

3 Vegetation Composition & Structure Climate & Population Change Disturbance (Wildfire, Bugs, Others) Biodiversity Carbon Others Invasive species Wildfire Specialist Climatologist Plant Scientist Insect Scientist Domain Modelers Remote Sensing Scientists GIS Specialists Statisticians Mathematicians Biodiversity Scientist Carbon Scientist CausesConsequences System of interest

4 Plant Growth Plant Dispersal Species Invasion Climate Change & Species Distribution Wildfire Carbon Biota Plant Satellite Imagery Environmental Field Ecologic Query & Integrate Plants Environmental Query & Integrate Transform & Integrate Data Flow – heterogeneous datasets/models/workflows

5 **Metaprovenance Provenance = dataset derivation – explicit information about which workflow components were used Metaprovenance = dataset derivation – capture tacit information about why those components were used and which components go together

6 For I = 1 to N Climate scenarios For j = 1 to N Algorithms Climate Workflow Wildfire Workflow Plant Growth Workflow System Workflow For k = 1 to N Parameter sets Other Subsystem Workflows Many output datasets Complex workflows/parameter sweeps

7 **Metaprovenance Project coordination Workflow => 1000 datasets Parameter sweep => 100 parameter sets Which dataset do I go to to see…??? Provenance = Given a dataset, what components/parameters were used? Metaprovenance = Given a set of components/parameters, which dataset was produced?

8 Science Dashboard? Enter project level information – project approach and design Control parameters

9 Abstract Workflow Executable Workflow Conceptual Model Scientist-Developer Collaboration Scientist- Developer Collaboration Vegetation Composition & Structure Climate Change Cognitive Networks Scientist-Scientist Collaboration Design Flow

10 Abstract Workflow Executable Workflow Cognitive Network Conceptual Model Formal Ontology Knowledge Flow Ontology-driven Workflows

11 Theory Experimental Design Empirical Results Data Analysis Inference Hypothesis Generation Conceptual Model Assumptions Idealizations Simplification Hypothesis testing Knowledge-Driven Workflows

12 Acknowledgments This work was heavily influenced by discussion within the SEEK project and especially the SEEK Knowledge Representation team. I appreciate all of their interaction. Only my own perspective is expressed, and they would not necessarily agree. The work was supported by National Science Foundation grant #0225665 for the Science Environment for Ecological Knowledge (SEEK) project and grant #0636317 for the CI-Team Demonstration Project: Advancing Cyberinfrastructure-Based Science through Education, Training, and Mentoring of Science Communities.


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