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—Broad access to the data on which scientific results are based is essential for verification, reproducibility, and extension. Scholarly publication has long been the means to this end. But as data volumes grow, new methods beyond traditional publications are needed for communicating, discovering, and accessing scientific data. We describe data publication(More)
Within and across thousands of science labs, researchers and students struggle to manage data produced in experiments, simulations, and analyses. Largely manual research data lifecycle management processes mean that much time is wasted, research results are often irreproducible, and data sharing and reuse remain rare. In response, we propose a new approach(More)
The efficiency and reliability of big data computing applications frequently depend on the ease with which they can manage and move large distributed data. For example, in x-ray science, both raw data and various derived data must be moved between experiment halls and archives, supercomputers, and user workstations for reconstruction, analysis,(More)
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