ICALEPCS2023 - List of Authors (Klingberg, J.M.)

Paper	Title	Page
WE3BCO08	Efficient and Automated Metadata Recording and Viewing for Scientific Experiments at MAX IV	1041
	D. van Dijken, V. Da Silva, M. Eguiraun, V. Hardion, J.M. Klingberg, M. Leorato, M. Lindberg MAX IV Laboratory, Lund University, Lund, Sweden
	With the advancements in beamline instrumentation, synchrotron research facilities have seen a significant improvement. The detectors used today can generate thousands of frames within seconds. Consequently, an organized and adaptable framework is essential to facilitate the efficient access and assessment of the enormous volumes of data produced. Our communication presents a metadata management solution recently implemented at MAX IV, which automatically retrieves and records metadata from Tango devices relevant to the current experiment. The solution includes user-selected scientific metadata and predefined defaults related to the beamline setup, which are integrated into the Sardana control system and automatically recorded during each scan via the SciFish[1] library. The metadata recorded is stored in the SciCat[2] database, which can be accessed through a web-based interface called Scanlog[3]. The interface, built on ReactJS, allows users to easily sort, filter, and extract important information from the recorded metadata. The tool also provides real-time access to metadata, enabling users to monitor experiments and export data for post-processing. These new software tools ensure that recorded data is findable, accessible, interoperable and reusable (FAIR[4]) for many years to come. Collaborations are on-going to develop these tools at other particle accelerator research facilities. [1] https://gitlab.com/MaxIV/lib-maxiv-scifish [2] https://scicatproject.github.io/ [3] https://gitlab.com/MaxIV/svc-maxiv-scanlog [4] https://www.nature.com/articles/sdata201618
	Slides WE3BCO08 [1.914 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-WE3BCO08
About •	Received ※ 06 October 2023 — Revised ※ 23 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 16 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Efficient and Automated Metadata Recording and Viewing for Scientific Experiments at MAX IV

1041

D. van Dijken, V. Da Silva, M. Eguiraun, V. Hardion, J.M. Klingberg, M. Leorato, M. Lindberg
MAX IV Laboratory, Lund University, Lund, Sweden

With the advancements in beamline instrumentation, synchrotron research facilities have seen a significant improvement. The detectors used today can generate thousands of frames within seconds. Consequently, an organized and adaptable framework is essential to facilitate the efficient access and assessment of the enormous volumes of data produced. Our communication presents a metadata management solution recently implemented at MAX IV, which automatically retrieves and records metadata from Tango devices relevant to the current experiment. The solution includes user-selected scientific metadata and predefined defaults related to the beamline setup, which are integrated into the Sardana control system and automatically recorded during each scan via the SciFish[1] library. The metadata recorded is stored in the SciCat[2] database, which can be accessed through a web-based interface called Scanlog[3]. The interface, built on ReactJS, allows users to easily sort, filter, and extract important information from the recorded metadata. The tool also provides real-time access to metadata, enabling users to monitor experiments and export data for post-processing. These new software tools ensure that recorded data is findable, accessible, interoperable and reusable (FAIR[4]) for many years to come. Collaborations are on-going to develop these tools at other particle accelerator research facilities.
[1] https://gitlab.com/MaxIV/lib-maxiv-scifish
[2] https://scicatproject.github.io/
[3] https://gitlab.com/MaxIV/svc-maxiv-scanlog
[4] https://www.nature.com/articles/sdata201618

Slides WE3BCO08 [1.914 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-WE3BCO08

About •

Received ※ 06 October 2023 — Revised ※ 23 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 16 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)