With the increasing volume and complexity of data produced by ultra-scale simulations and high-throughput experiments, understanding the science is largely hampered by the lack of comprehensive, end-to-end data management solutions ranging from initial data acquisition to final analysis and visualization. The Scientific Data Management (SDM) Center is bringing a set of advanced data management technologies to DOE scientists in various application domains including astrophysics, climate, fusion, and biology. Equally important, it has established collaborations with these scientists to better understand their science as well as their forthcoming data management and data analytics challenges. The SDM center has provided advanced data managemen...
Modern science is most often driven by data. Improvements in state-of-the-art technologies and metho...
International audienceThe novel and multidisciplinary data centric and scientific movement promises ...
Many scientific applications have large I/O requirements, in terms of both the size of data and the ...
With the increasing volume and complexity of data produced by ultra-scale simulations and high-thro...
Managing scientific data has been identified by the scientific community as one of the most importan...
Dealing with the volume, complexity, and diversity of data currently being generated by scientific e...
Our contributions to advancing the state‐of‐the‐art in scientific workflows have f...
Science--like business, national security, and even everyday life--is becoming more and more data in...
Studying the scientific data infrastructure (SDI) that is needed to produce, store, transmit, manage...
Visualization is a highly data intensive science: visualization algorithms take as input vast amount...
Scientific user facilities---particle accelerators, telescopes, colliders, supercomputers, light sou...
Scientists in all fields face challenges in managing and sustaining access to their research data. T...
This is the final report from SDSC and UC Davis on DE-FC02-01ER25486, Scientific Data Management Int...
Digitalization has opened doors for science not only to discuss the results of their research, but a...
Many scientific applications are I/O intensive and gen-erate large data sets, spanning hundreds or t...
Modern science is most often driven by data. Improvements in state-of-the-art technologies and metho...
International audienceThe novel and multidisciplinary data centric and scientific movement promises ...
Many scientific applications have large I/O requirements, in terms of both the size of data and the ...
With the increasing volume and complexity of data produced by ultra-scale simulations and high-thro...
Managing scientific data has been identified by the scientific community as one of the most importan...
Dealing with the volume, complexity, and diversity of data currently being generated by scientific e...
Our contributions to advancing the state‐of‐the‐art in scientific workflows have f...
Science--like business, national security, and even everyday life--is becoming more and more data in...
Studying the scientific data infrastructure (SDI) that is needed to produce, store, transmit, manage...
Visualization is a highly data intensive science: visualization algorithms take as input vast amount...
Scientific user facilities---particle accelerators, telescopes, colliders, supercomputers, light sou...
Scientists in all fields face challenges in managing and sustaining access to their research data. T...
This is the final report from SDSC and UC Davis on DE-FC02-01ER25486, Scientific Data Management Int...
Digitalization has opened doors for science not only to discuss the results of their research, but a...
Many scientific applications are I/O intensive and gen-erate large data sets, spanning hundreds or t...
Modern science is most often driven by data. Improvements in state-of-the-art technologies and metho...
International audienceThe novel and multidisciplinary data centric and scientific movement promises ...
Many scientific applications have large I/O requirements, in terms of both the size of data and the ...