Transcript Rapid Prototyping Capability for Earth

Rapid Prototyping Capability
for Earth-Sun System Sciences
Robert J. Moorhead
Mississippi State University
5 Sept 2006
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
Approach
A systems engineering approach will be used to
integrate 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
Applied Sciences Systems Engineering Environment
Solutions
Network
Candidate
Research
Results
Rapid
Prototyping
Capability
Evaluated
Research
Results
Integrated
Systems
Solutions
for
Integrated
System
Solutions
Operations
or
Operations
Pre-Evaluation
Evaluation
Verification/Validation
Benchmark
From “Extending NASA Earth-Sun System Research Results through a Systems Engineering
Capacity,” Working Document, NASA Applied Sciences Program
5 Sept 2006
MRC RPC Approach
• Decide on some prototype RPC experiments
• Implement a system
• Run experiments
5 Sept 2006
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
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
5 Sept 2006
5 Sept 2006
RPC system
concept
• Good for explaining
functionality
• Problem:
Vertically integrated
5 Sept 2006
RPC should be horizontally integrated
Reason: scalability, robustness, maintenance, extensibility
5 Sept 2006
Example
Data Service
access control
storage service
transport service
5 Sept 2006
metadata catalog
transformations
Jane’s home
or airport
lounge
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, …
Current State
5 Sept 2006
RPC ideas
•
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
5 Sept 2006
Hierarchical from
the catalog of catalogs
to local storage
(including remote
RPC nodes)
Uniquely describes
the data sets
needed
regardless
if they exist or not
Current Vision
Could be IGE tools
or models or
other data product processing
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), or
5 Sept
2006(and procedures) to experts.
generate a request for creation
of data
RPC notes
5 Sept 2006
MRC RPC website
• http://www.gri.msstate.edu/research/nasa_rpc
5 Sept 2006