1. Themes in Geosciences

2. 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
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

3. 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

4. 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

5. 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

6. 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

7. 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