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Astro / Geo / Eco - Sciences

Astro / Geo / Eco - Sciences. Illustrative examples of success stories: S loan digital sky survey: data portal for astronomy data, 1M + users and nearly 1B queries. Sunfall : visual analytics tool for astrophysics . ACE: argumentation/abduction system to support paleolandform dating

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Astro / Geo / Eco - Sciences

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  1. Astro / Geo / Eco - Sciences Illustrative examples of success stories: • Sloan digital sky survey: data portal for astronomy data,1M+ users and nearly 1B queries. • Sunfall: visual analytics tool for astrophysics. • ACE: argumentation/abduction system to support paleolandform dating • Prometheus: system for ecological modeling. • eBirds: crowdsourcing project for species distribution and migration modeling • ALERTS: Automated Land change Evaluation, Reporting and Tracking System

  2. Astronomy Large Synoptic Sky Telescope (LSST) starts operation in 2018, will collect ~100PB of data within a decade • Challenges • 10’s of TB of data, 70K anomalies per night • Tracking and classifying objects and events (possibly unknown) • Opportunities • Go beyond detection, to discovery of general theories/concepts • Real-time alerting of discoveries • Hybrid (human and automated) control of instruments • Coordination of crowd-sourced science

  3. Forensic Paleoclimatology NOAA Paleoclimatology Archive contains 7K cores up to 3km long, with 13 proxies measured at millimeter intervals • Challenges • Determine what happened to a set of unobserved variables over the course of time under the influence of (potentially unknown) processes • Reconstruct and align the temporal history of material in core data of different types (glaciers, ocean sediments, trees) at different spatial and temporal scales • Handle multiple competing hypotheses, model and data uncertainty • Opportunities • Improve reconstruction of past history of the climate • Deduce causality and patterns in the global climate system • Make better predictions about future climate • Evaluating potential interventions

  4. Earth Sciences Climate Model Intercomparison Project version 5 (CMIP5) expected to reach 2-3PB by 2013, satellites collect observations at high spatial and temporal resolutions • Challenges • Automatically identify (potentially constrained, generalized) patterns, causal relationships from large spatio-temporal datasets • Simulations and observations – assimilation of data and models • Provide interactive, highly responsive visualizations • Opportunities • Generate hypotheses for the underlying physical mechanisms • Improve prediction and forecasting across temporal scales • Early warning for transient events (e.g., hurricanes, tsunamis)

  5. Cross-Cutting Themes • Does “big science” have limits? Do have to go back to smaller groups but armed with better tools? • “Anomaly detection” – requires powerful representation of current knowledge combined with social dimension to evaluate science, tools for replication, sharing, collaboration • Integration of data, models, and a priori knowledge • “Active Learning” for experiment / data selection, automated planning & control • Representation of scientific arguments, consensus & controversy • Understand communication among scientists, build tools to facilitate both collaboration and analysis tasks

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