@article{lakshminarasimhan_shah_ethier_ku_chang_klasky_latham_ross_samatova_2013, title={ISABELA for effective in situ compression of scientific data}, volume={25}, ISSN={["1532-0634"]}, DOI={10.1002/cpe.2887}, abstractNote={SUMMARY}, number={4}, journal={CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE}, author={Lakshminarasimhan, Sriram and Shah, Neil and Ethier, Stephane and Ku, Seung-Hoe and Chang, C. S. and Klasky, Scott and Latham, Rob and Ross, Rob and Samatova, Nagiza F.}, year={2013}, pages={524–540} }
 @article{schendel_jin_shah_chen_chang_ku_ethier_klasky_latham_ross_et al._2012, title={ISOBAR Preconditioner for Effective and High-throughput Lossless Data Compression}, ISSN={["1084-4627"]}, DOI={10.1109/icde.2012.114}, abstractNote={Efficient handling of large volumes of data is a necessity for exascale scientific applications and database systems. To address the growing imbalance between the amount of available storage and the amount of data being produced by high speed (FLOPS) processors on the system, data must be compressed to reduce the total amount of data placed on the file systems. General-purpose loss less compression frameworks, such as zlib and bzlib2, are commonly used on datasets requiring loss less compression. Quite often, however, many scientific data sets compress poorly, referred to as hard-to-compress datasets, due to the negative impact of highly entropic content represented within the data. An important problem in better loss less data compression is to identify the hard-to-compress information and subsequently optimize the compression techniques at the byte-level. To address this challenge, we introduce the In-Situ Orthogonal Byte Aggregate Reduction Compression (ISOBAR-compress) methodology as a preconditioner of loss less compression to identify and optimize the compression efficiency and throughput of hard-to-compress datasets.}, journal={2012 IEEE 28TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE)}, author={Schendel, Eric R. and Jin, Ye and Shah, Neil and Chen, Jackie and Chang, C. S. and Ku, Seung-Hoe and Ethier, Stephane and Klasky, Scott and Latham, Robert and Ross, Robert and et al.}, year={2012}, pages={138–149} }
 @inproceedings{jenkins_arkatkar_lakshminarasimhan_boyuka_schendel_shah_ethier_chang_chen_kolla_et al., title={ALACRITY: Analytics-driven lossless data compression for rapid in-situ indexing, storing, and querying}, volume={8220}, booktitle={Transactions on large-scale data- and knowledge- centered systems x: special issue on database- and expert-systems applications}, author={Jenkins, J. and Arkatkar, I. and Lakshminarasimhan, S. and Boyuka, D. A. and Schendel, E. R. and Shah, N. and Ethier, S. and Chang, C. S. and Chen, J. and Kolla, H. and et al.}, pages={95–114} }
 @book{lakshminarasimhan_shah_ethier_klasky_latham_ross_n.f., title={Compressing the Incompressible with ISABELA:
In-situ Reduction of Spatio-Temporal Data}, journal={Technical Report- Not held in TRLN member libraries}, author={Lakshminarasimhan, S. and Shah, N. and Ethier, S.J and Klasky, S. and Latham, R. and Ross, R. and N.F., Samatova} }