Environmental data are being generated and collected at unprecedented rates. However, the diversity in form and format of these environmental assets poses challenges for collaborative and reproducible science. Moreover, access constraints that surround environmental data lead to difficulty in use and interpretation of results. Cloud computing offers high potential to break down such barriers and engender collaboration, attribution, reuse, and reproducibility. In this article we review the design of the Environmental Virtual Observatory pilot (EVOp) that was conceived as a cloud-enabled virtual research space for different users interested in environmental science, ranging from domain specialists to the general public. We discuss the key technologies and processes used: a hybrid cloud infrastructure; standard service interfaces; a unified service delivery platform; and a test-driven development cycle. We also discuss the methodology by showcasing one of the exemplars developed in EVOp, stressing the importance of weaving stakeholder engagement from the beginning and throughout the process. We also briefly highlight some of the lessons learnt of working in an interdisciplinary team.
Results are presented from a new web application called OceanDIVA-Ocean Data lntercomparison and Visualization Application. This tool reads hydrographic profiles and ocean model output and presents the data on either depth levels or isotherms for viewing in Google Earth, or as probability density functions (PDFs) of regional modeldata misfits. As part of the CLIVAR Global Synthesis and Observations Panel, an intercomparison of water mass properties of various ocean syntheses has been undertaken using OceanO IV A. Analysis of model-data misfits reveals significant differences between the water mass properties of the syntheses, such as the ability to capture mode water properties. AUTHORS' BIOGRAPHIES Dr Alastair Gemmell holds a DPhil in Geochemistry and works on the visualisation and comparison of large marine datasets at the Reading e-Science Centre at Reading University, and with other partner institutes of the National Centre for Ocean Forecasting. Dr Greg Smith holds a PhD in physical oceanography and is currently a Postdoctoral Fellow at the University of Reading's Environmental Systems Science Centre. He formerly worked as a Postdoctoral Fellow at the lnstitut des Sciences de Ia Mer at the University of Quebec in Rimouski (UQAR) after receiving his doctorate from McGill University.
Abstract. As part of a large European coastal operational oceanography project (ECOOP), we have developed a web portal for the display and comparison of model and in situ marine data. The distributed model and in situ datasets are accessed via an Open Geospatial Consortium Web Map Service (WMS) and Web Feature Service (WFS) respectively. These services were developed independently and readily integrated for the purposes of the ECOOP project, illustrating the ease of interoperability resulting from adherence to international standards.The key feature of the portal is the ability to display coplotted timeseries of the in situ and model data and the quantification of misfits between the two. By using standardsbased web technology we allow the user to quickly and easily explore over twenty model data feeds and compare these with dozens of in situ data feeds without being concerned with the low level details of differing file formats or the physical location of the data.Scientific and operational benefits to this work include model validation, quality control of observations, data assimilation and decision support in near real time. In these areas it is essential to be able to bring different data streams together from often disparate locations.
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