SAMPLE TRACKING

ENABLING TECHNOLOGIES

178 ESRF

The COVID-19 pandemic has accelerated the need for large-scale remote and mail-in access solutions for user experiments, and especially the ability to accurately track large numbers of samples and tools transiting through the facility. In only a few months, a sample tracking module has been developed and implemented in an existing module (ICAT+) of the metadata catalogue ICAT.

M. Guijarro. ESRF

Special thanks to BLISS developers: W. De Nolf (DAU), B. Formet, M. Guijarro, C. Guilloud, P. Guillou, D. Mammeri, L. Pithan, S. Petitdemange, V. Valls. Special thanks to BCU members: G. Berruyer, A. Beteva, L. Claustre, S. Debionne, S. Fisher, A. Homs, R. Homs, M-C. Lagier, A. Mauro, J. Meyer, C. Muzelle, M. Oskarsson, E. Papillon, H. Witsch, and to A. Goetz and A. Sole.

[1] M. Guijarro et al., Proc. ICALEPCS 17, Barcelona, Spain (2017). [2] https://www.certif.com/content/spec/ [3] https://code.google.com/p/icatproject/ [4] http://pan-data.eu/ [5] https://redis.io/ [6] J.M. Meyer et al., Proc. PCaPAC 12, Kolkata, India (2012). [7] M. Könnecke et al., J. Appl. Cryst. 48, 301-305 (2015). [8] https://github.com/silx-kit/silx [9] https://www.gevent.org [10] https://gitlab.esrf.fr/bliss/bliss.git

AUTHOR

ACKNOWLEDGEMENTS

REFERENCES

BLISS is built around the asynchronous Input/ Output (I/O) programming paradigm. Data acquisition being mainly an I/O-bound task, the choice has been made to achieve concurrency using asynchronous I/O coupled with an event loop and callbacks, built on top of gevent [9]. As a result, BLISS implements cooperative

multitasking, which reduces race conditions, locking issues and general problems linked with pre-emptive context switching.

As of today, although BLISS core features already cover the basic and advanced needs of a majority of ESRF beamlines, BLISS is still actively developed. For example, the support of diffractometer geometries and reciprocal space calculations will be enhanced in the next months and years. One important area of improvement is to extend the capabilities of BLISS for online data analysis by storing data in an online buffer. This will allow online data compression before writing data to disk and help address the data avalanche expected with the EBS. Quality assurance is a strong value within the BLISS development team: any code added to BLISS has to pass through the 2000+ tests of the Continuous Integration pipeline, and those are constantly improved and extended. The team s commitment is to deliver a high-quality, certified scientific software, reliable and maintainable in the long term. BLISS is free to use by anyone, and contributions are welcome. The project home is accessible online [10].

Fig. 154: Online data visualisation with Flint.

It was already on the agenda at the ESRF as part of the STREAMLINE H2020 project to extend and promote remote and mail-in access for experiments that are amenable to this. The ESRF has been using ISPyB (Information System for Protein crYstallography Beamlines, https://

www.esrf.eu/ispyb) for many years as an excellent Laboratory Information Management System (LIMS) and sample tracking interface for structural biology experiments (crystallography, BioSAXS and cryo-EM). For non-structural biology experiments, sample tracking has been