The NANOOS Visualization System (NVS): lessons learned in data aggregation, management and reuse, for a user application

Abstract

The mission of NANOOS is to coordinate and support the development, implementation, and operations of a regional coastal ocean observing system (RCOOS) for the Pacific Northwest region, as part of the U.S. IOOS. A key objective for NANOOS is to provide data and user-defined products to a diverse group of stakeholders in a timely fashion, and at spatial and temporal scales appropriate for their needs. To this end, NANOOS developed the NANOOS Visualization System (NVS), which aggregates, displays and serves meteorological and oceanographic data, derived from buoys, gliders, tide gauges, HF Radar, meteorological stations and satellites, as well as model forecast information in such a way that it presents end users with a rich, informative and user friendly experience. First released in November 2009, NVS has already undergone several significant updates. While its original focus and continued strength is on near-real-time (NRT) observations from stationary platforms (buoys, coastal stations, etc.), it has evolved to include other types of observations as well as forecast information. NVS integrates data from a wide diversity of providers across the region, ranging from county agencies, private industry and regional partnerships, to core IOOS federal programs, and state agencies and academic groups that are principal partners in NANOOS' Data Management and Communication (DMAC) efforts. Regional and national feedback confirms that NVS has been well received by ocean observing and stakeholder communities alike. This paper discusses, in detail, NVS 2.0, which was released in August 2010. In particular, we provide an in depth look at the database schema, metadata, data harvesting, and component communication. In addition, we discuss the NVS data management and communication approach in the context of the IOOS DMAC interoperability and standards-based efforts, highlighting the strengths and weaknesses of application-focused vs. strong-interoperability-focused approaches. Lessons learned both from technical and project management perspectives are also presented. Lastly, we discuss future plans for NVS. Anticipated improvements include automating asset metadata discovery and processing using IOOS standard protocols, and a NANOOS implementation of ERDDAP that will support NVS by replacing multiple, data-source-specific data harvesters with more generic and easier-to-maintain NERDDAP harvesters; and by enabling customized data subsetting and download capabilities that will be accessible through the NVS user interface.