University of Cambridge > Talks.cam > Behaviour, Ecology & Evolution Seminar Series > Big Data Meets Geo-Computation: Combining Research Reproducibility and Processing Efficiency in High-performance Computing

Big Data Meets Geo-Computation: Combining Research Reproducibility and Processing Efficiency in High-performance Computing

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In recent years there has been an explosion of geo-datasets derived from an increasing number of remote sensors, field instruments, sensor networks, and other GPS -equipped “smart” devices. “Big Data” processing requires flexible tools that combine efficient processing, either on your local pc or on remote servers (e.g, clusters – HPCs). However, leveraging these new data streams requires new tools and increasingly complex workflows often involving multiple software and/or programming languages. This also the case for GIS and Remote Sensing analysis where statistical/mathematical algorithms are implemented in complex geospatial workflows. I will show few examples of environmental applications where I combine different open-source geo-libraries for a massive computation at Yale Center for Research Computing using High Performance Computing platform.

This talk is part of the Behaviour, Ecology & Evolution Seminar Series series.

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