"Big data" has become a major force of research progress in HPC-based data mining and innovation across enterprises of all sizes. A lot of new platforms with increasingly more features for managing big datasets have been proposed recently. Big Data mining is also related to the management of cloud and modern HPC clusters. Quality assurance in Big Data mining in such systems is the important research and engineering challenge in today's data intensive computing. Quality in Big Data systems can be directly related to the quality of data - poor quality data is predominant in many such systems. The velocity of Big Data directly refers to data quality problems. On the other hand, Big Data processing and analytics requires high quality services and resource and data management tools.
In this thematic track, we expect new concepts and research results addressing all quality issues in Big Data Systems. Suggested topics of interest include, but are not restricted to:
Thematic Track Committee
Track Chairs:
Track PC Members:
Joanna Kołodziej
Joanna Kołodziej is the Professor in Research and Academic Computer Network (NASK) Institute. She is also the Head of the Department of Computer Sciences at Cracow University of Technology. Prof. Kolodziej serves as the President of the Polish Chapter of IEEE Computational Intelligence Society. She participated in several international and national projects including ECONET, 7FP and PARAPHRASE 7FP Grants. Currently, she is the Chair of the cHiPSet Cost Action IC1406 (chipset-cost.eu).
Sabri Pllana
Sabri Pllana is currently an Associate Professor at the Dept. of Computer Science of the Linnaeus University in Sweden. He has published over 70 peer-reviewed scientific papers. His research interests include heterogeneous parallel computing systems, and cognitive computing techniques for learning parallel programming. He contributed to several EU-funded projects and he coordinated the FP7 project PEPPHER. He is associate editor of Computing journal (Springer), and a Senior Member of the IEEE.