The Science Data Understanding Group carries out research and
development in computational techniques to extract knowledge from
science data.
We believe that new computational capabilities, from detectors to flight
and ground computers through to the Internet, are revolutionizing the
way science phenomena are captured as digital data, the way knowledge is
extracted from these data, and the way data and knowledge are exchanged
by the scientific community.
What we do: Model the behavior and
statistical variability of physical systems like
oceans and atmospheres, recognize patterns in very large
data sets taken from such systems, and distribute resulting data in a
grid or virtual observatory context.
Our work covers these general topic areas:
Physical Modeling and Inversion
- Inversion of cosmic microwave background to recover structural
parameters of the universe (Wilkinson Microwave Anisotropy Probe and
Planck)
- Assessment of climate model agreement
- Data assimilation and Bayesian risk assessment for highly
nonlinear weather systems
- Spacecraft trajectory generation with noise and uncertainty
models
Data Mining and Pattern Recognition
- Developed a leading system for recognizing, grouping, and tracking
solar active regions used for SOHO (Solar and Helioseismic Observatory)
and SDO (Solar Dynamics Observatory)
- Developed multi-observation summarized data products for MISR
and AIRS, which has been deployed as a L3 data product
- Spatial data fusion and interpolation for atmospheric fields in
a Bayesian context
- Pattern recognition, obstacle classification, terrain
classification for autonomous rover navigation (DARPA, ARO)
- Anomaly detection, search, and behavior classification in engineering time series from ISS (ESMD)
Web Services, Virtual Observatories, Data Fusion
- Data fusion for MISR aerosols, being deployed to Langley DAAC
- GIS for Mars landing site selection; GIS for California water flow analysis
- Generation of whole-Earth Landsat mosaics and deployment as web service (OnEarth), with extensions to Moon and Mars
- Science-grade sky mosaicking as a grid service as a component of NVO
- Classification of astronomical events and follow-up observation recommendation in a grid context for NVO
