Testing the US Integrated Ocean Observing System Data Discovery and Distribution Infrastructure with Real-World Problems

Wednesday, 17 December 2014: 10:35 AM
Derrick Preston Snowden1, Rich Signell2, Kelly Knee3, John Kupiec4, Andy Bird3, Bob Fratantonio3, Will Koeppen5 and Kyle Wilcox5, (1)NOAA, US Integrated Ocean Observing System, Boulder, CO, United States, (2)USGS Woods Hole Science Center, Woods Hole, MA, United States, (3)RPS/ASA, South Kingstown, RI, United States, (4)LMI, Reston, VA, United States, (5)Axiom Data Science LLC, Anchorage, AK, United States
The distributed, service-oriented architecture of the US Integrated Ocean Observing System (US IOOS) has been implemented mostly independently by US IOOS partners, using different software approaches and different levels of compliance to standards. Some uniformity has been imparted by documenting the intended output data formats and content and service interface behavior. But to date, a rigorous testing of the distributed system of systems has not been done. To assess the functionality of this system, US IOOS is conducting a system integration test ( that evaluates whether the services (i.e. SOS, OPeNDAP, WMS, CS/W) deployed to the 17 Federal partners and 11 Regional Associations can solve real-world problems. Scenarios were selected that both address IOOS societal goals and test different functionality of the data architecture. For example, one scenario performs an assessment of water level forecast skill by prompting the user for a bounding box and a temporal extent, searching metadata catalogs via a Catalog Services for the Web (CS/W) interface to discover available sea level observations and model results, extracting data from the identified service endpoints (either OPeNDAP or SOS), interpolating both modeled and observed data onto a common time base, and then comparing the skill of the various models. Other scenarios explore issues such as hypoxia and wading bird habitats. For each scenario, the entire workflow (user input, search, access, analysis and visualization) is captured in an IPython Notebook on GitHub. This allows the scenarios to be self-documenting as well as reproducible by anyone, using free software. The Python packages required to run the scenarios are all available on GitHub and Conda packages are available on so that users can easily run the scenarios using the free Anaconda Python distribution. With the advent of hosted services such as Wakari, it is possible for anyone to reproduce these workflows for free, without installing any software locally, using just their web browser. Thus in addition to performing as a system integration test, this project serves to provide examples that anyone in the geoscience community can adapt to solve other real-world problems.