Rapid Prototyping Capability for Earth-Sun System Sciences

1. Rapid Prototyping Capabilityfor Earth-Sun System Sciences Robert J. Moorhead Mississippi State University 5 Sept 2006

2. Approach Formulate architectures and develop baseline capacities that integrate applied sciences systems tools into configurations to support efficient evaluation of the prospects of integrating research results from NASA’s Earth observation systems (with emphasis on spacecraft instruments on missions recently launched or planned for near-term launch) and associated Earth system models • systems engineering tools • enterprise architecture tools • information visualization and analysis tools • uncertainty characterization tools • performance assessment tools “NASA Earth Science and Space Systems benefiting Society: Evolving Systems Engineering Capacity,” presentation by Ron Birk, August 24, 2005, SSC 5 Sept 2006

3. Approach A systems engineering approach will be used tointegrate and evolve the engineering and analysis tools necessary to efficiently evaluate candidate research results, through a rapid prototyping capability, to further determine potential solutions for assimilation into operational decision support processes and enable the community to propose projects for feasible solutions using innovative NASA research results. From “Extending NASA Earth-Sun System Research Results through a Systems Engineering Capacity,” Working Document, NASA Applied Sciences Program 5 Sept 2006

4. Solutions Network Operations Integrated Systems Solutions Candidate Research Results Evaluated Research Results Rapid Prototyping Capability for Integrated System Solutions or Operations Verification/Validation Benchmark Pre-Evaluation Evaluation Applied Sciences Systems Engineering Environment From “Extending NASA Earth-Sun System Research Results through a Systems Engineering Capacity,” Working Document, NASA Applied Sciences Program 5 Sept 2006

5. MRC RPC Approach • Decide on some prototype RPC experiments • Implement a system • Run experiments 5 Sept 2006

6. RPC prototype experiments • Agricultural Efficiency (Chuck O'Hara) • Land Information System (Val Anantharaj) • Watershed Modeling (Chuck O'Hara) • Invasive Species (Lori Bruce) • SERVIR (Greg Easson) 5 Sept 2006

7. Operational Scenario Summary • Design the experiment – identify the models and data sets to be used • Assess whether the models and data are currently integrated with the RPC node • Make requests to model and data specialists, as needed; the specialists issue a notification when the models and data are available • Configure the experiment (establish the model parameters) • Run (and monitor) the model • Analyze the results 5 Sept 2006

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10. RPC system concept • Good for explainingfunctionality • Problem:Vertically integrated 5 Sept 2006

11. RPC should be horizontally integrated Reason: scalability, robustness, maintenance, extensibility 5 Sept 2006

12. Example Data Service access control storage service transport service metadata catalog transformations 5 Sept 2006

13. Jane’s home or airportlounge Stennis MSU Data Service Goddard Data Service Replica management access control storage service transport service metadata catalog transformations logging fault recovery 5 Sept 2006 Discovery, brokerage, …

14. Current State 5 Sept 2006

15. Make things happen faster by cumulating knowledge: Standards for describing data (metadata system) If I can describe what I need, I should be able to: Locate the data, if exist Access the data (local or remote storage, data providers, …) Request creation of the data (simulated data, models, …) This requires separation of metadata and data (metadata for nonexistent files) No conflict with data having headers The headers can be used for automatic generation of metadata Haupt has a mandate and expertise to work on the metadata schemas and expertise to build the infrastructure to support it. Procedures of accessing data Data providers (DAAC, NOAA, etc.) Simulated data “generators” and/or repositories Derived data products Procedures of processing data Workflow definition and enacting (data and control flow, with fault recovery) Capturing parameters and arguments Execution is distributed environment Loosely coupled tools and other software artifacts (interactive and batch) Integrated environments (“glue-ware”) Do not accumulate data Data providers, data access centers have mandate for that There is not enough disk space available We need policies and procedures for cleaning “scratch”/”workspace” areas RPC ideas 5 Sept 2006

16. Current Vision Hierarchical fromthe catalog of catalogs to local storage(including remoteRPC nodes) Could be IGE tools or models or other data product processing Uniquely describesthe data setsneeded regardlessif they exist or not Integrated Environment Verify the selection • Workspace caches the data needed for the analysis • Tools operate on workspace • Tools can be organized into workflows • Glueware simplifies data flow from one component to another • Glueware simplifies the management of the workspace • Glueware generates metadata and provenance • Glueware simplifies adding data to repositories The selected data set (data manager) are dropped onto workspace. This triggers creating a local link, downloading from remote repository or data providers, submitting batch processing (recursively), orgenerate a request for creation of data (and procedures) to experts. 5 Sept 2006

17. RPC notes 5 Sept 2006

18. MRC RPC website • http://www.gri.msstate.edu/research/nasa_rpc 5 Sept 2006