1 TB raw image data classification + 1 TB analytical results per 3D image, 1 PB data per moderated hospital per year 18 Medical diagnostic Volume of data Multi-modal imaging with Scalable key-value and Machine learning (support Computational imaging around 70 PB acquisition disparate channels of data object store databases; vector machine [SVM] and Bioimaging annually, 32 TB on requires HPC back ImageJ, OMERO, random forest [RF]) for emerging machines end VolRover, advanced classification and for a single scan segmentation and recommendation services feature detection methods 19 >100 TB in 1 to 2 ≈300 GB of File formats not Open-source Processing of raw data to Genomic years at NIST, many compressed though some sequencing produce variant calls, Measurements PBs in healthcare data/day standards exist; generally bioinformatics clinical interpretation of community generated by DNA structured data software from variants sequencers academic groups 20 50 TB New sequencers Biological data that are Standard Descriptive statistics, Comparative stream in data at inherently heterogeneous, bioinformatics tools statistical significance in Analysis for growing rate complex, structural, and (BLAST, HMMER, hypothesis testing, data Metagenomes hierarchical; besides core multiple alignment and clustering and classification and Genomes genomic data, new types of phylogenetic tools, omics data such as gene callers, sequence transcriptomics, feature predictors), methylomics, and proteomics Perl/Python wrapper scripts 21 5 million patients Not real time but 100 controlled vocabulary HDFS supplementing Integration of data into Individualized updated values and 1,000 continuous Mayo internal data semantic graphs, using Diabetes periodically values per patient, mostly warehouse (EDT) graph traverse to replace Management time-stamped values SQL join; development of semantic graph-mining algorithms to identify graph patterns, index graph, and search graph; indexed Hbase; custom
1 TB raw image data + 1 TB analytical results per 3D image, 1 PB data per moderated hospital per year classification 18 Computational Bioimaging Medical diagnostic imaging around 70 PB annually, 32 TB on emerging machines for a single scan Volume of data acquisition requires HPC back end Multi-modal imaging with disparate channels of data Scalable key-value and object store databases; ImageJ, OMERO, VolRover, advanced segmentation and feature detection methods Machine learning (support vector machine [SVM] and random forest [RF]) for classification and recommendation services 19 Genomic Measurements >100 TB in 1 to 2 years at NIST, many PBs in healthcare community ≈300 GB of compressed data/day generated by DNA sequencers File formats not though some standards exist; generally structured data Open-source sequencing bioinformatics software from academic groups Processing of raw data to produce variant calls, clinical interpretation of variants 20 Comparative Analysis for Metagenomes and Genomes 50 TB New sequencers stream in data at growing rate Biological data that are inherently heterogeneous, complex, structural, and hierarchical; besides core genomic data, new types of omics data such as transcriptomics, methylomics, and proteomics Standard bioinformatics tools (BLAST, HMMER, multiple alignment and phylogenetic tools, gene callers, sequence feature predictors), Perl/Python wrapper scripts Descriptive statistics, statistical significance in hypothesis testing, data clustering and classification 21 Individualized Diabetes Management 5 million patients Not real time but updated periodically 100 controlled vocabulary values and 1,000 continuous values per patient, mostly time-stamped values HDFS supplementing Mayo internal data warehouse (EDT) Integration of data into semantic graphs, using graph traverse to replace SQL join; development of semantic graph-mining algorithms to identify graph patterns, index graph, and search graph; indexed Hbase; custom