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Data Analysis WorkbeNch ( DAWN )

2015; Wiley; Volume: 22; Issue: 3 Linguagem: Inglês

10.1107/s1600577515002283

1600-5775

Mark Basham, Jacob Filik, Michael T. Wharmby, Peter Chang, Bahá El Kassaby, Matthew Gerring, Jun Aishima, Karl Levik, Bill Pulford, Irakli Sikharulidze, Duncan Sneddon, Matthew J. Webber, S. S. Dhesi, Francesco Maccherozzi, Olof Svensson, Sándor Brockhauser, Gabor Náray, Alun Ashton,

Machine Learning in Materials Science

Synchrotron light source facilities worldwide generate terabytes of data in numerous incompatible data formats from a wide range of experiment types. The Data Analysis WorkbeNch ( DAWN ) was developed to address the challenge of providing a single visualization and analysis platform for data from any synchrotron experiment (including single-crystal and powder diffraction, tomography and spectroscopy), whilst also being sufficiently extensible for new specific use case analysis environments to be incorporated ( e.g. ARPES, PEEM). In this work, the history and current state of DAWN are presented, with two case studies to demonstrate specific functionality. The first is an example of a data processing and reduction problem using the generic tools, whilst the second shows how these tools can be targeted to a specific scientific area.