Data Intensive Computing
Intelligent Compression for Multidimensional Data Volumes
Principal Investigator: Nathaniel Beagley
Challenge
Generating massive volumes of streaming experimental data leads to cumbersome data storage and analysis
Approach
Develop a rapid compression methodology that allows direct extraction of segments of the data volume, without uncompressing the entire file
Impact
Researchers will be able to store data in compressed form (allowing for speed and size) and have greatly increased efficiency in data analysis tasks
Collaborations
- Ion mobility spectrometer (IMS) research team (EMSL/FCSD)
Accomplishments
- Prototype compression / retrieval methodology
- Testing and requirements analysis on IMS data
Multidimensional Data Volumes