SLAC, Menlo Park, California, USA
BNL, Upton, Long Island, New York, USA
ORNL, Oak Ridge, Tennessee, USA
DLS, Oxfordshire, United Kingdom
ANL, Argonne, Ilinois, USA
ESS, Lund, Sweden
ITER Organization, St. Paul lez Durance, France
Cosylab, Ljubljana, Slovenia
FRIB, East Lansing, Michigan, USA
BNL, Upton, Long Island, New York, USA
A typical experiment involves not only the raw data from a detector, but also requires additional data from the beamline. This information is largely kept separated and manipulated individually, to date. A much more effective approach is to integrate these different data sources, and make these easily accessible to data analysis clients. NSLS-II data flow system contains multiple backends with varying data types. Leveraging the features of these (metadatastore, filestore, channel archiver, and Olog), this library provides users with the ability to access experimental data. This service acts as a single interface for time series, data attribute, frame data access and other experiment related information.
BNL, Upton, Long Island, New York, USA
The beamlines at NSLS-II are among the highest instrumented, and controlled of any worldwide. Each beamline can produce unstructured data sets in various formats. This data should be made available for data analysis and processing for beamline scientists and users. Various data flow systems are in place in numerous synchrotrons, however these are very domain specific and cannot handle such unstructured data. We have developed a data flow service, metadatastore, that manages experimental data in NSLS-II beamlines. This service enables data analysis and visualization clients to access this service either directly or via databroker api in a consistent and partition tolerant fashion, providing a reliable and easy to use interface to our state-of-the-art beamlines.
BNL, Upton, Long Island, New York, USA
NSLS-II beamlines can generate 72,000 data sets per day resulting in over 2 M data sets in one year. The large amount of data files generated by our beamlines poses a massive file management challenge. In response to this challenge, we have developed filestore, as means to provide users with an interface to stored data. By leveraging features of Python and MongoDB, filestore can store information regarding the location of a file, access and open the file, retrieve a given piece of data in that file, and provide users with a token, a unique identifier allowing them to retrieve each piece of data. Filestore does not interfere with the file source or the storage method and supports any file format, making data within files available for NSLS-II data analysis environment.
