1. SDM Center Techniques for feature identification in scientific data Chandrika Kamath (LLNL) with Erick Cantú-Paz, Imola Fodor, Cyrus Harrison, Nicole Love, Siddharth Manay, Dale Slone (LLNL, funded by SciDAC) and Domain scientists: Ben Santer (LLNL), Keith Burrell and Mike Walker (GAT), Neil Pomphrey, Don Monticello, Stewart Zweben (PPPL)

2. SDM Center Sapphire software for scientific data mining RDB: Data Store User Input & Feedback Components linked by Python De-noise data Background- subtraction Identify objects Extract features Sample data Fuse data Multi-resolution- analysis Data items Features Normalization Dimension- reduction Decision trees Neural Networks SVMs k-nearest neighbors Clustering Evolutionary algorithms Tracking …. FITS BSQ PNM View... Display Patterns Sapphire Software Public Domain Software Sapphire & Domain Software Work funded by NNSA ASC, LDRD, SciDAC

3. SDM Center Our capabilities Analysis of data from simulations, experiments, and observations A three-fold focus analysis of data from practical problems using modular, extensible software which incorporates research in robust, accurate, scalable algorithms Our expertise includes image and video processing, pattern recognition, statistical techniques, machine learning, … Analyzed datasets ranging from megabytes to terabytes in domains ranging from experimental physics to astronomy, remote sensing, fluid-mix problems, information retrieval, video surveillance, climate, …

4. SDM Center Our early work funded by SciDAC Identifying features connected to edge-harmonic oscillations in DIII-D Tokamak Separating signals in climate data

5. SDM Center Current work: characterization of Poincaré plots Exploring two techniques Piecewise polynomial method Graph-based KAM algorithm Current status Implemented graph library to replace Boost KAM as-is unlikely to work on our data Unclear if techniques are robust to the diversity of data

6. SDM Center Current work: characterization and tracking of coherent structures Exploring two techniques Image segmentation Motion estimation Current status Applied techniques to various sets of images Preparing summary report for discussion with PPPL

7. SDM Center Future work Characterization of Poincaré plots Combining the two techniques Extracting other features for orbit classification Fine-tuning parameters for accurate classification Extracting separatrix and island widths Deploying the software Characterization and tracking of coherent structures Implement techniques to extract statistics of coherent structures. Refine algorithms to identify and track the structures Identify other applications for analysis