22

33

ROMS/COAWST NcML fileROMS/COAWST NcML file

44

55

Exploiting IOOS: A Distributed, Standards-Based Framework and

Software Stack for Searching, Accessing, Analyzing and Visualizing Met-Ocean Data

Exploiting IOOS: A Distributed, Standards-Based Framework and

Software Stack for Searching, Accessing, Analyzing and Visualizing Met-Ocean Data

Rich Signell (USGS-CMG)Filipe Fernandes (SECOORA)

Kyle Wilcox (Axiom Data Science)Andrew Yan (USGS-CIDA)

Rich Signell (USGS-CMG)Filipe Fernandes (SECOORA)

Kyle Wilcox (Axiom Data Science)Andrew Yan (USGS-CIDA)

Regional IOOS DMAC Meeting: Silver Spring, 5/28/2015

ObjectivesObjectives

• Set up a standards-based framework for easy and efficient access to insitu and ocean model data

• Provide a high-level search and browse web interface for program datasets, for scientists, end users and program managers

• Contribute to a growing standardized data search, access and use infrastructure that supports all geoscience

• Set up a standards-based framework for easy and efficient access to insitu and ocean model data

• Provide a high-level search and browse web interface for program datasets, for scientists, end users and program managers

• Contribute to a growing standardized data search, access and use infrastructure that supports all geoscience

Why not just use ERDDAP?Why not just use ERDDAP?

• Two reasons:• 1. Unstructured grid models• 2. Curvilinear grid models

• Two reasons:• 1. Unstructured grid models• 2. Curvilinear grid models

UGRID Conventions on GitHubUGRID Conventions on GitHub

SGRID Conventions: github/sgridSGRID Conventions: github/sgrid

IOOS Model Data Interoperability DesignIOOS Model Data Interoperability Design

ROMS

ADCIRC

HYCOM

SELFE

NCOM NcML

NcML

NcML

NcML

NcML

Common Data Model

OPeNDAP+CF

WCS

NetCDF Subset

THREDDS Data Server

Standardized (CF-1.6, UGRID-0.9) Virtual Datasets

NonstandardModel Output Data Files

Web Services Matlab

Panoply

IDV

Clients

NetCDF-Java

Libraryor Broker

WMS

ncISO

ArcGIS

NetCDF4-Python

FVCOM

PythonERDDAP

NetCDF-Java

SOS

Geoportal Server

GeoNetwork

GI-CAT

Observed data (buoy, gauge, ADCP, glider)

Godiva2

pycsw-CKANNcML

GridUgridTimeSeriesProfileTrajectoryTimeSeriesProfile

NonstandardData Files

CatalogServices

Interoperable Model Comparison in Matlab(using nctoolbox)

Interoperable Model Comparison in Matlab(using nctoolbox)

compare_secoora_model_sections.mcompare_secoora_model_sections.m

3D visualization of data with IDV3D visualization of data with IDV

NECOFS Access in ArcGIS(using the dap2arc python toolbox)

NECOFS Access in ArcGIS(using the dap2arc python toolbox)

USGS CMG PortalUSGS CMG Portal

NetCDF Point Subset ServiceNetCDF Point Subset Service

Iris Python tools from the UK Met OfficeIris Python tools from the UK Met Office

Automated model comparisonAutomated model comparison

Getting your model results connectedGetting your model results connected

• Find someone with a THREDDS Data Server or install your own

• Drop your files in a directory, and add an NcML file that starts with “00_dir” (e.g. “00_dir_roms.ncml”) to aggregate, standardize and describe the dataset: Sample ROMS NcML file

• If you want your data to end up in the portal, add “CMG_Portal” to the “project” attribute: <attribute name=“project”value=“CMG_Portal”/>

• If you want your datasets to be discoverable, submit a PR on list of thredds catalogs being scanned on github

• Full instructions on the USGS-CMG Portal Github Wiki

• Find someone with a THREDDS Data Server or install your own

• Drop your files in a directory, and add an NcML file that starts with “00_dir” (e.g. “00_dir_roms.ncml”) to aggregate, standardize and describe the dataset: Sample ROMS NcML file

• If you want your data to end up in the portal, add “CMG_Portal” to the “project” attribute: <attribute name=“project”value=“CMG_Portal”/>

• If you want your datasets to be discoverable, submit a PR on list of thredds catalogs being scanned on github

• Full instructions on the USGS-CMG Portal Github Wiki

A few problems… PackagingA few problems… Packaging

• Ipython notebooks are a great way to document model skill assessment workflows (Filipe will talk about this)

• But python environment uses a lot of tricky packages. How to make this easy for folks?

• Conda and binstar to the rescue! (Filipe will talk about this)

• Ipython notebooks are a great way to document model skill assessment workflows (Filipe will talk about this)

• But python environment uses a lot of tricky packages. How to make this easy for folks?

• Conda and binstar to the rescue! (Filipe will talk about this)

A few problems… WMSA few problems… WMS

• ncWMS works great for CF compliant data• Unstructured grids are not CF compliant.• Staggered grids are not CF compliant. • ncWMS doesn’t work for unstructured grid data

(FVCOM, ADCIRC, SELFE), and doesn’t work for staggered grid velocities in models like ROMS, WRF and Delft3D

• sci-wms to the rescue, using UGRID conventions for unstructured grid (pyugrid), and SGRID conventions for staggered grid (pysgrid). (Kyle will talk about this)

• ncWMS works great for CF compliant data• Unstructured grids are not CF compliant.• Staggered grids are not CF compliant. • ncWMS doesn’t work for unstructured grid data

(FVCOM, ADCIRC, SELFE), and doesn’t work for staggered grid velocities in models like ROMS, WRF and Delft3D

• sci-wms to the rescue, using UGRID conventions for unstructured grid (pyugrid), and SGRID conventions for staggered grid (pysgrid). (Kyle will talk about this)

Key Infrastructure ComponentsKey Infrastructure Components

• Common data models for “feature types” (structured, staggered and unstructured grids, time series, profiles, swaths) (Unidata CDM, UGRID, SGRID)

• Standard web data services for delivering these common data model “feature types” (OPeNDAP/CF/UGRID/SGRID, WMS, SOS, WFS, ERDDAP/tabledap, ERDDAP/griddap)

• Standard catalog services for the metadata (OGC CSW, OpenSearch)

• Tools for easy delivery of data in standard services

• Tools for easy search, access and use of data in standard services (in all major environments: Python, ArcGIS, R, Matlab, JavaScript)

• Common data models for “feature types” (structured, staggered and unstructured grids, time series, profiles, swaths) (Unidata CDM, UGRID, SGRID)

• Standard web data services for delivering these common data model “feature types” (OPeNDAP/CF/UGRID/SGRID, WMS, SOS, WFS, ERDDAP/tabledap, ERDDAP/griddap)

• Standard catalog services for the metadata (OGC CSW, OpenSearch)

• Tools for easy delivery of data in standard services

• Tools for easy search, access and use of data in standard services (in all major environments: Python, ArcGIS, R, Matlab, JavaScript)

Infrastructure BenefitsInfrastructure Benefits

• What are the benefits?– Less time wasted messing with data,

more time spent on science– More skill assessment of models– More usage and more appropriate

useage of model results – Faster feedback to modelers =>

improved models– Better science, better models =>better

world

• What are the benefits?– Less time wasted messing with data,

more time spent on science– More skill assessment of models– More usage and more appropriate

useage of model results – Faster feedback to modelers =>

improved models– Better science, better models =>better

world