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Title
Enabling Geo Data Portal (GDP) functionality for commonly used scientic analysis environments
primary contact/s:
Curtis Price, Dave Blodgett, Rich Signell
Description
Project Topic |
Tasks |
Resources Required |
Major Outcomes |
Total Funding Needed |
Python and Matlab port of GDP client tools (WPS) w/ hooks for ArcGIS Toolbox |
Develop python functions to execute GDP web processing services
Develop python based ArcGIS Toolbox to return GDP data products |
~1 month python developer
~1 month Matlab developer
~1 month ArcGIS developer
Travel Funds for two, three-day face to face meetings. |
Python scripting tools and ArcGIS toolbox to access GDP web processing services. |
Travel $ money for face to face planning and development
~$5k-10k
Funds for contract developer salary
~3 Months FTE |
Additional Criteria
- No ArcGIS or other software required
- Python 2.5, 2.7 etc
Benefit to FSP/Scientists/Mission Areas
The creation of a python module will allow many commonly-used scientific software tools (ArcGIS, Python, R, Matlab, Microsoft Office) to access GDP analysis functionality. The GDP is now acessible through an interactive web page, which is another system to learn and data formats to navigate.
In kind funding and work leveraged
- Opens CIDA's Geo Data Portal functionality to scientific app clients
Interaction with DMWG
Review of software distribution for appropriate metadata, policy implications
Deliverable and its Measurable Benefit
- Python module supported on Windows, Linux (Ubuntu), OS X
Methodology (process)
- Proposed Functionality
Return list of preloaded GDP gridded data sets
Allow user-defined OPeNDAP URL as input
Validate OPeNDAP URL as valid gridded data
Return ranges of lon,lat,time and height (describe grid)
Return available statistical techniques
Return available preloaded shapefiles
Interface to ArcGIS with validated inputs
Inputs:
Allow specification of lon/lat range, time range and depth/height range
Allow specification of statistical techniques
Allow specification of shapefile or polygon as array (numpy)
Output:
Returns calculated time and summary statistical data as arrays (numpy)
- Design
Co-developed with end users and contractor via agile development approach (1 week iteration for 4 weeks)
- Coding
A contractor with experience with Python will write the python module. Curtis will do the ArcGIS interface work.
- Distribution/publishing
- Include in USGS ArcGIS distribution, available on all USGS ArcGIS Desktops
- Open Source
- Ubuntu Distribution (Personal Package Archive)
Partnerships
NOAA Southwest Fisheries Science Center - Environmental Research Division (SWFSC-ERD)
Geo Data Portal project (CIDA)
Interagency Coastal Marine Spatial Planning (CMSP) Group