Exploring Large Marine Datasets Using an Interactive Website and Google Earth
Jonathan D Blower, Daniel Bretherton, Keith Haines, Chunlei Liu, Adit Santokhee
Reading e-Science Centre, University of Reading, ESSC, Harry Pitt Building, 3 Earley Gate, Whiteknights, Reading RG6 6AL, United Kingdom
In this presentation we shall discuss our experiences with using Google Maps and Google Earth to explore and visualize oceanographic data. We focus on data from General Circulation Model analyses of ocean circulation for operational and research purposes. These datasets are produced by institutions such as the UK Met Office and the National Oceanography Centre and are very valuable, both for environmental science research and for applications such as search and rescue and oil spill mitigation. It is important for scientists to be able to explore and visualize these high-resolution, terabyte-scale datasets efficiently; it is also important from an educational point of view to allow novice users to be able to explore these datasets in order to understand the ocean circulation. Geobrowsers such as Google Earth are promising tools for achieving this but have important limitations. These include a lack of proper treatment of the depth and time dimensions: geobrowsers mainly focus on surface features that do not vary with time.
We present a system that works around these limitations by combining the geobrowser with an interactive website: this is known as the ``Godiva2'' system. The website allows the user to select the dataset and variable of interest (e.g.\ sea water temperature as predicted by the Met Office), then select the water depth and time. The website includes an instant preview of the data in a dynamic map component (a Google Map). Having selected the required parameters, the user clicks on a link to display the data in Google Earth. The user can zoom into the virtual globe and data will be displayed at an appropriate resolution, allowing users to see features of ocean circulation at all scales. Displayed images are all generated dynamically from source data, giving a high degree of flexibility (e.g.\ user-defined colour scales). We shall discuss the design of the system and the lessons learned, concluding with a discussion of work in progress and future work, including our work towards basing the system upon international, open standards such as the Open Geospatial Consortium's Web Map Service.