ICALEPCS2023 - List of Authors (Leorato, 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)

THMBCMO02	Enhancing Data Management with SciCat: A Comprehensive Overview of a Metadata Catalogue for Research Infrastructures	1195
	C. Minotti, A. Ashton, S.E. Bliven, S. Egli PSI, Villigen PSI, Switzerland F.B. Bolmsten, M. Novelli, T.S. Richter ESS, Lund, Sweden M. Leorato MAX IV Laboratory, Lund University, Lund, Sweden D. McReynolds LBNL, Berkeley, California, USA L.A. Shemilt RFI, Didcot, United Kingdom
	As the volume and quantity of data continue to increase, the role of data management becomes even more crucial. It is essential to have tools that facilitate the management of data in order to manage the ever-growing amount of data. SciCat is a metadata catalogue that utilizes a NoSQL database, enabling it to accept heterogeneous data and customize it to meet the unique needs of scientists and facilities. With its API-centric architecture, SciCat simplifies the integration process with existing infrastructures, allowing for easy access to its capabilities and seamless integration into workflows, including cloud-based systems. The session aims to provide a comprehensive introduction of SciCat, a metadata catalogue started as a collaboration between PSI, ESS, and MAXIV, which has been adopted by numerous Research Infrastructures (RIs) worldwide. The presentation will delve into the guiding principles that underpin this project and the challenges that it endeavours to address. Moreover, it will showcase the features that have been implemented, starting from the ingestion of data to its eventual publication. Given the growing importance of the FAIR (Findable, Accessible, Interoperable, and Reusable) principles, the presentation will touch upon how their uptake is facilitated and will also provide an overview of the work carried out under the Horizon 2020 EU grant for FAIR.
	Slides THMBCMO02 [5.158 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO02
About •	Received ※ 05 October 2023 — Revised ※ 09 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 20 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

THMBCMO09	DAQ System Based on Sardana and PandABox for Combined SAXS, Fluorescence and UV-Vis Spectroscopy Techniques at MAX IV CoSAXS Beamline
	V. Da Silva, R. Appio, M. Eguiraun, F. Herranz-Trillo, A.F. Joubert, M. Leorato, Y.L. Li, M. Lindberg, C. Takahashi, A.E. Terry MAX IV Laboratory, Lund University, Lund, Sweden C. Dicko Lund Institute of Technology (LTH), Lund University, Lund, Sweden W.T. Kitka S2Innovation, Kraków, Poland
	CoSAXS is the Coherent and Small Angle X-ray Scattering (SAXS) beamline placed at the diffraction-limited 3 GeV storage ring at MAX IV Laboratory. This paper presents the data acquisition (DAQ) strategy for combined SAXS, Ultraviolet-visible (UV-Vis) and Fluorescence Spectroscopy techniques. In general terms, the beamline control system is based on TANGO and on top of it, Sardana provides an advanced scan framework. Sardana performs the experiment orchestration, configuring and preparing the X-ray detector and the Spectrometers for UV-Vis and Fluorescence. Hardware triggers are used to synchronize the DAQ for the different techniques running simultaneously. The implementation is done using PandABox, which generates pulse trains for the X-ray detector and spectrometers. PandABox integration into the system is done with a Sardana Trigger Gate Controller, used to configure the pulse trains parameters as well to orchestrate the hardware triggers during a scan. This paper describes the individual techniques’ integration into the control system, the experiment orchestration and synchronization and the new experiment possibilities this multi-technique DAQ system brings to MAX IV beamlines.
	Slides THMBCMO09 [0.570 MB]
	Poster THMBCMO09 [1.600 MB]
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

FR2BCO03	Taranta Project - Update and Current Status	1657
	Y.L. Li, M. Eguiraun, J. Forsberg, V. Hardion, M. Leorato MAX IV Laboratory, Lund University, Lund, Sweden V. Alberti INAF-OAT, Trieste, Italy M. Canzari INAF - OAAB, Teramo, Italy A. Dubey PSL, Pune, India M. Gandor, D.T. Trojanowska S2Innovation, Kraków, Poland H.R. Ribeiro Universidade do Porto, Faculdade de Ciências, Porto, Portugal
	Taranta, developed jointly by MAX IV Laboratory and SKA Observatory, is a web based no-code interface for remote control of instruments at accelerators and other scientific facilities. It has seen a great success in system development and scientific experiment usage. In the past two years, the panel of users has greatly expanded. The first generation of Taranta was not able to handle the challenges introduced by the user cases, notably the decreased performance when a high number of data points are requested, as well as new functionality requests. Therefore, a series of refactoring and performance improvements of Taranta are ongoing, to prepare it for handling large data transmission between Taranta and multiple sources of information, and to provide more possibilities for users to develop their own dashboards. This article presents the status of the Taranta project from the aspects of widgets updates, packages management, optimization of the communication with the backend TangoGQL, as well as the investigation on a new python library compatible with the newest python version for TangoGQL. In addition to the technical improvements, more facilities other than MAX IV and SKAO are considering to join Taranta project. One workshop has been successfully held and there will be more in the future. This article also presents the lesson learned from this project, the road map, and the GUI strategy for the near future.
	Slides FR2BCO03 [4.759 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-FR2BCO03
About •	Received ※ 06 October 2023 — Accepted ※ 21 November 2023 — Issued ※ 23 November 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)

THMBCMO02

Enhancing Data Management with SciCat: A Comprehensive Overview of a Metadata Catalogue for Research Infrastructures

1195

C. Minotti, A. Ashton, S.E. Bliven, S. Egli
PSI, Villigen PSI, Switzerland
F.B. Bolmsten, M. Novelli, T.S. Richter
ESS, Lund, Sweden
M. Leorato
MAX IV Laboratory, Lund University, Lund, Sweden
D. McReynolds
LBNL, Berkeley, California, USA
L.A. Shemilt
RFI, Didcot, United Kingdom

As the volume and quantity of data continue to increase, the role of data management becomes even more crucial. It is essential to have tools that facilitate the management of data in order to manage the ever-growing amount of data. SciCat is a metadata catalogue that utilizes a NoSQL database, enabling it to accept heterogeneous data and customize it to meet the unique needs of scientists and facilities. With its API-centric architecture, SciCat simplifies the integration process with existing infrastructures, allowing for easy access to its capabilities and seamless integration into workflows, including cloud-based systems. The session aims to provide a comprehensive introduction of SciCat, a metadata catalogue started as a collaboration between PSI, ESS, and MAXIV, which has been adopted by numerous Research Infrastructures (RIs) worldwide. The presentation will delve into the guiding principles that underpin this project and the challenges that it endeavours to address. Moreover, it will showcase the features that have been implemented, starting from the ingestion of data to its eventual publication. Given the growing importance of the FAIR (Findable, Accessible, Interoperable, and Reusable) principles, the presentation will touch upon how their uptake is facilitated and will also provide an overview of the work carried out under the Horizon 2020 EU grant for FAIR.

Slides THMBCMO02 [5.158 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-THMBCMO02

About •

Received ※ 05 October 2023 — Revised ※ 09 October 2023 — Accepted ※ 14 December 2023 — Issued ※ 20 December 2023

Cite •

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

THMBCMO09

DAQ System Based on Sardana and PandABox for Combined SAXS, Fluorescence and UV-Vis Spectroscopy Techniques at MAX IV CoSAXS Beamline

V. Da Silva, R. Appio, M. Eguiraun, F. Herranz-Trillo, A.F. Joubert, M. Leorato, Y.L. Li, M. Lindberg, C. Takahashi, A.E. Terry
MAX IV Laboratory, Lund University, Lund, Sweden
C. Dicko
Lund Institute of Technology (LTH), Lund University, Lund, Sweden
W.T. Kitka
S2Innovation, Kraków, Poland

CoSAXS is the Coherent and Small Angle X-ray Scattering (SAXS) beamline placed at the diffraction-limited 3 GeV storage ring at MAX IV Laboratory. This paper presents the data acquisition (DAQ) strategy for combined SAXS, Ultraviolet-visible (UV-Vis) and Fluorescence Spectroscopy techniques. In general terms, the beamline control system is based on TANGO and on top of it, Sardana provides an advanced scan framework. Sardana performs the experiment orchestration, configuring and preparing the X-ray detector and the Spectrometers for UV-Vis and Fluorescence. Hardware triggers are used to synchronize the DAQ for the different techniques running simultaneously. The implementation is done using PandABox, which generates pulse trains for the X-ray detector and spectrometers. PandABox integration into the system is done with a Sardana Trigger Gate Controller, used to configure the pulse trains parameters as well to orchestrate the hardware triggers during a scan. This paper describes the individual techniques’ integration into the control system, the experiment orchestration and synchronization and the new experiment possibilities this multi-technique DAQ system brings to MAX IV beamlines.

Slides THMBCMO09 [0.570 MB]

Poster THMBCMO09 [1.600 MB]

Cite •

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

FR2BCO03

Taranta Project - Update and Current Status

1657

Y.L. Li, M. Eguiraun, J. Forsberg, V. Hardion, M. Leorato
MAX IV Laboratory, Lund University, Lund, Sweden
V. Alberti
INAF-OAT, Trieste, Italy
M. Canzari
INAF - OAAB, Teramo, Italy
A. Dubey
PSL, Pune, India
M. Gandor, D.T. Trojanowska
S2Innovation, Kraków, Poland
H.R. Ribeiro
Universidade do Porto, Faculdade de Ciências, Porto, Portugal

Taranta, developed jointly by MAX IV Laboratory and SKA Observatory, is a web based no-code interface for remote control of instruments at accelerators and other scientific facilities. It has seen a great success in system development and scientific experiment usage. In the past two years, the panel of users has greatly expanded. The first generation of Taranta was not able to handle the challenges introduced by the user cases, notably the decreased performance when a high number of data points are requested, as well as new functionality requests. Therefore, a series of refactoring and performance improvements of Taranta are ongoing, to prepare it for handling large data transmission between Taranta and multiple sources of information, and to provide more possibilities for users to develop their own dashboards. This article presents the status of the Taranta project from the aspects of widgets updates, packages management, optimization of the communication with the backend TangoGQL, as well as the investigation on a new python library compatible with the newest python version for TangoGQL. In addition to the technical improvements, more facilities other than MAX IV and SKAO are considering to join Taranta project. One workshop has been successfully held and there will be more in the future. This article also presents the lesson learned from this project, the road map, and the GUI strategy for the near future.

Slides FR2BCO03 [4.759 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-FR2BCO03

About •

Received ※ 06 October 2023 — Accepted ※ 21 November 2023 — Issued ※ 23 November 2023

Cite •

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