Title: OceanXtremes: Oceanographic Data-Intensive Anomaly Detection and Analysis Portal
Presenting Author: Thomas Huang
Organization: Jet Propulsion Laboratory
Co-Author(s): Edward Armstrong, George Chang, Toshio Chin, Brian Wilson, Tong Lee and Victor Zlotnicki

Abstract:
The authors will present the concept plans and preliminary design for an oceanographic anomaly detection platform and web portal called OceanXtremes. OceanXtremes will be powered by an intelligent, analytic service backend infused on a Hybrid Cloud Computing environment to execute domain-specific, multi-scale anomaly and feature detection algorithms across the entire archive of ocean science datasets. OceanXtremes will be equipped with both web portal and web service interfaces for users and applications/systems to register and retrieve oceanographic anomalies data. By leveraging technology such as Datacasting (Bingham, 2007), users can also subscribe to anomaly or “event” types of their interest and have newly computed anomaly metrics and other information delivered to them by metadata feeds packaged in standard Rich Site Summary (RSS) format. Upon receiving new feed entries, users can examine the metrics and download relevant variables, by simply clicking on a link, to begin further analyzing the event. The OceanXtremes web portal will allow users to define their own anomaly or feature types where continuous backend processing will be scheduled to populate the new user-defined anomaly type by executing the chosen data mining algorithm (i.e. differences from climatology or gradients above a specified threshold). Metadata on the identified anomalies will be cataloged including temporal and geospatial profiles, key physical metrics, related observational artifacts and other relevant metadata to facilitate discovery, extraction, and visualization. Importantly, although the system will be established with these selected datasets, it will be readily extendable to satellite collections, which could support additional science disciplines (e.g., ecosystems science, the carbon community, or terrestrial satellite and in situ observations).