An expandable web-based platform for visually analyzing basin-scale hydro-climate time series data

Joeseph P Smith,Timothy S Hunter,Anne H Clites,Craig A Stow,Tad Slawecki,Glenn C Muhr,Andrew D Gronewold

doi:10.1016/j.envsoft.2015.12.005

Abstract

Growing demand from the general public for centralized points of data access and analytics tools coincides with similar, well-documented needs of regional and international hydrology research and resource management communities. To address this need within the Laurentian Great Lakes region, we introduce the Great Lakes Dashboard (GLD), a dynamic web data visualization platform that brings multiple time series data sets together for visual analysis and download. The platform's adaptable, robust, and expandable Time Series Core Object Model (GLD-TSCOM) separates the growing complexity and size of Great Lakes data sets from the web application interface. Although the GLD-TSCOM is currently applied exclusively to Great Lakes data sets, the concepts and methods discussed here can be applied in other geographical and topical areas of interest.

Highlights

Many previously available data services advertised as Great Lakes data or containing Great Lakes data were exclusive to the United States, leaving out Canadian data, which are invaluable for Great Lakes basin-wide data and model output
Amidst growth in collected data, establishment of large, central data discovery and distribution services, and demand for simple access and visualization of aggregate data, we have developed applications based on a single model that fulfill needs within the Laurentian Great Lakes data user communities
We have considered and incorporated the demands of many stakeholders, researchers, and managers in the Great Lakes community

Summary

Introduction

Two notable efforts include the Consortium of Universities for the Advancement of Hydrologic Science, Inc. Hydrologic Information System (CUAHSI-HIS, Horsburgh et al (2009)) and the Great Lakes Observing System (GLOS, Read et al (2010)). Hydrologic Information System (CUAHSI-HIS, Horsburgh et al (2009)) and the Great Lakes Observing System (GLOS, Read et al (2010)) Both projects focus on providing access to and documentation for point observation data, as opposed to aggregate (e.g. averages e over temporal, spatial domains, or both) data. Access is realized through web services, with CUAHSI HIS implementing a propietary Observations Data Model (ODM, Horsburgh et al (2008)) via a Relational Database Management System (RDBMS), and GLOS utilizing tools compliant with Open Geospatial Consortium (OGC, see Web References section) standards

Methods

Results

Conclusion