Themes in Geosciences

Collecting Data Geology in the cloud Crowdsourcing data collection Link sensed data from the field to repositories Crowdsourcing data collection Community coordinated modeling & science portals People as sensors Eg http://mping.nssl.noaa.gov Autonomous sensor platforms Regulations on privacy and control Combine imaging with priors on features for fluid imaging From motion to 3D topography Challenges in geospace Limitations on the min values that can be measured Small scales: time step and grid size Strongly-driven non-linear system BABAIE TIKOFF RIDLEY HOREL HSU RAVELA HOREL RIDLEY

Integrating Data Open data / software sharing Facilitates reuse of data Growing set of geographic data services High quality open, free software Fusion, synthesis, integration Mediation through brokering Lack of trustworthiness indicators On-time integration of data Rank and combine models Topical mapping with semantic web Semantic linking across datasets & types Intelligent data cleaning, classification, comparison Automate what an expert would do Machine-intelligent computational systems that compare scientific hypotheses and stochastic dynamical models Intelligent “filtering” PETERS YARMEY POPE PIERCE LERMUSIAUX TIKOFF HILL BABAIE PIERCE PETERS BABAIE PIERCE POPE TIKOFF YARMEY LERMUSIAUX KINTER

Analyzing Data Applications for uncertainty analysis Pattern recognition Smart queries to large data repositories for dynamic pattern recognition Pattern theory for fluids Analyze heterogeneous, dynamic, “messy” data Systems that help one understand different datasets. Improve reproducibility Tools for rapid comparison, data checks Improve trustworthiness and relevance of “discovered data” RIDLEY LERMUSIAUX HILL HOREL RAVELA HOREL TIKOFF HILL RIDLEY YARMEY

Processing Data Advances in High Performance Infrastructure substantial increase in high-performance computing (HPC) resources Improved synthesis for high volume data among distributed archive and processing centers Automated, distributed workflow Accessibility to large data CI systems that can allow users access to data that they cannot generate, but can use KINTER RIDLEY POPE HILL TIKOFF

Visualizing Data Multidimensional data vis 3D profiles (e.g. for stratigraphic profiles) Discovery of features Machine learning, data analytics, advanced visualization for big datasets Visualizing integrated data and models Use treemaps Semantic and topical analysis Match with multi-attributed outputs with large data vis Immersive vis and interactive tangibles Interactive and immersive simulation/games BABAIE KINTER LERMUSIAUX PIERCE PIERCE HILL

Cross Cutting Themes Education, Engagement, Community Foster cross-disciplinary training Building the IS-GEO community Outreach across the spectrum of stakeholders HSU HILL PIERCE Humans as part of the Observing System Subjective choices in geoscience workflows Choices in the selection of software and data processing tools Uncertainty, values, interpretation and variability Crowd sourcing and citizen science HOREL TIKOFF PANKRATIUS PIERCE Machine reading and learning Rapid finding, extracting, organizing data PETERS