Kenton McHenry

There is a growing need to bring together large data collections and analytics, such as those based on machine learning, to create needed derived data products from unstructured sensor data, such as satellite data, to identify characteristics of permafrost across the Arctic region such as ice-wedge polygons, thaw slumps, and coastal erosion. These derived products in turn provide researchers with another data resource which can be leveraged and or combined to study permafrost degradation and how it is tied to climate from the sub-meter to the pan-Arctic scales. To facilitate this type of science and connect the wide range of needed tools, data, and infrastructure within the scientific community we are establishing a scientific gateway, the Permafrosts Discovery Gateway (PDG), which will provide a convenient user friendly web based interface by which researchers can create, explore, and utilize this big data. The technology being leveraged to establish this gateway includes Clowder, an NSF funded open source data management framework designed for broad reuse and customizability having been used by a number of such resources across a variety of scientific domains. We will describe the Clowder framework and how the various community tools, visualizations, and infrastructure resources (e.g. computational and data/archival) are brought together within it to establish the PDG.