Content from this work may be used under the terms of the CC BY 4.0 licence (© 2023). Any distribution of this work must maintain attribution to the author(s), title of the work, publisher, and DOI

19th Int. Conf. Accel. Large Exp. Phys. Control Syst.
ICALEPCS2023, Cape Town, South Africa
JACoW Publishing
ISBN: 978-3-95450-238-7
ISSN: 2226-0358
doi:10.18429/JACoW-ICALEPCS2023-THPDP101

CREATING OF HDF5 FILES AS DATA SOURCE FOR ANALYSES USING
THE EXAMPLE OF ALPS IIc AND DOOCS CONTROL SYSTEM
S. Karstensen1 , P. Gonzalez-Caminal3, G. Günther2, A. Lindner1, O. Mannix2, I. Oceano1,V. Rybnikov1, K. Schwarz1, G. Sedov1
1
DESY Hamburg, Germany
2
Helmholtz-Zentrum Berlin für Materialien und Energie GmbH (HZB), Germany
3
Fusion for Energy (ATG Science & Technology, S.L.), Barcelona, Spain
Abstract
A versatile and graphical HDF5 file generation project.
In the realm of physical experiments, data is typically gathered through the utilization of measurement devices intricately integrated into control systems. These control systems employ diverse methods for archiving historical data.
Nevertheless, users consistently grapple with a recurring
challenge: how to access the data, decipher the intricaciesof the control system's structure, and understand the formatting. The prevailing approach involves the creation ofscripts or programs tasked with extracting data from thesecontrol systems, and if necessary, followed by the requisite
data pre-processing for subsequent analysis. Typically, thispre-processing is carried out in formats known exclusively
to the individual user. Moreover, the longevity of data utility often teeters on the brink when users depart or deviate
from established conventions.
To address these challenges, we are actively developing
software that serves a dual purpose: firstly, to provide an
API for a control system (in this instance, DOOCS), andsecondly, to transform the extracted data into a universally
recognized format, such as HDF5, complete with all relevant metadata.
The ALPS IIc experiment serves as an ideal testbench
for this software development task due to its compatibility
in terms of state and timing.

ABOUT HDF5
The Hierarchical Data Format Version 5 (HDF5) 0 is aunique high-performance technology suite that consists ofan abstract data model, library, and file format for storingand managing extremely large and/or complex data collections. The technology is used worldwide by government,industry, and academia in a wide range of science, engineering, and business disciplines.

Advantages of HDF5
 Versatile data model that can represent very complex,
heterogeneous data objects and a wide variety of
metadata through an unlimited variety of datatypes.
 Ready for high-speed raw data acquisition Portable and extensible with no limits on file size, allowing applications to evolve in their use of HDF5.

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 Self-describing, requiring no outside information forapplications to interpret the structure and contents ofa file.
 Robust software ecosystem of open-source tools andapplications for managing, manipulating, viewing,and analyzing data.
 Architecturally independent software library that runs
on a wide range of computational platforms (from laptops to massively parallel systems) and programming
languages (including C, C++, Fortran 90, and Java interfaces) Advanced performance features that allow for accesstime and storage space optimizations through customizable product packaging, compression, and encryption
 Long-term data archiving solution
 Self-explaining data structure

METADATA
Metadata is structured data that contains overarching information about a resource. Metadata is used to describe
the measured data (measurement data) with additional information, enabling their machine and automated processing, as well as providing insight into their origin andimproving understanding. Taking metadata into account in
the analysis can lead to better results.
Metadata could include: Process-specific information
 Images, Log Files, Links
 Hazards
 Responsible Users Storage Location
 Information about locations
 Permissions
 Publications
 Derived Objects
 Comments
 Hardware information
 eLogbook entries
 And many other information

SoftwareData Management

HDF5 GENERATORThe HDF5 Generator is an innovative software productcurrently under development by DESY in Hamburg. Itserves as a bridge between experiments, control systems,
and databases, seamlessly transforming collected data into
a new HDF5 file.
Figure 1 provides a comprehensive overview of theHDF5 data generation process.

parameters as required for complex accelerator operations(Fig. 3).

CONTROL SYSTEM

Automatic HDF5 file structure generator
Controlsystem
dataProcessor

APIGUI for graphical definition of theHDF5 containing datameasurement values
from control system.json output forPython file.json
Configfile

HDF5
staticFinal HDF5 file

PBS / EDMS

APIMetaData

Get Experiment
information fromEDMS

Main task to combine all partsand create HDF5

Create Metadata for GUIand HDF5 fileFigure 3: DOOCS control system schema.
Figure 1: Principle of HDF5 generator.

To the left, control system data is received and meticulously processed via an API. Metadata containing essential
information about the control system data and setup of thewhole experiment for potential source reconstruction, follows a parallel procedure. Additionally, certain metadata
serves the crucial role of furnishing users with a tailoredgraphical interface, simplifying the process of data selection. These elements are seamlessly amalgamated by theprocessor and subsequently archived as an HDF5 file.
Actually, we are working on a first version of the HDF
generator. First tests are made and they are promising.

DOOCS is based on a distributed client-server architecture combined with a device-oriented view. The devices arethe basic entities and can be virtual integrated software instruments or real ones with hardware attached. Each control system parameter is made accessible via network calls
through a device application.
Its transportation layer is based on the standardized, industrial RPC protocol and allows for a robust and efficient
data transfer. Support for integrating a timing systemproviding clock, trigger and other time-based accelerator
information is built-in into the core software and comfortably accessible within the framework.

GUI CAPABILITIESDETECTOR AND DATA SOURCE

The graphical interface (Fig. 2) encompasses all experiment-related devices and channels, providing the user
with the capability to choose which data to record in theHDF5 file. Each data value is supplemented with metadata,facilitating precise one-to-one associations. The graphicalstructure is documented and stored in a JSON file, ensuring
a well-defined structure for ease of reading. As a proof ofconcept, we initially utilized Node-RED to conduct a feasibility analysis, with the final product slated to feature adistinct GUI.

The Any Light Particle Search II (ALPS II) 0, picturedin Fig. 4 , is a light-shining-through-a-wall (LSW) experiment based at DESY in Hamburg, Germany, that will
search for axions and axion-like particles down to the coupling of the axion to two photons of gaγγ >2 x 10−11 GeV−1
for masses below 0.1 meV. ALPS II will use two strings ofsuperconducting dipole magnets that are over one hundred
meters in length, as well as optical cavities before and after
the wall to boost the effective signal rate of the regenerated
photons by more than 12 orders of magnitude when compared to previous generations of LSW experiments. Datataking with a simplified optical system has started in May
2023.

Figure 2: GUI interface and json output.
The Distributed Object-Oriented Control System DOOCS - provides a versatile software framework for creating accelerator-based control system applications 0.
These can range from monitoring simple temperature sensors up to high-level controls and feedback of beam
SoftwareData Management

Figure 4: ALPS IIc at DESY, length: 280 m.

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Content from this work may be used under the terms of the CC BY 4.0 licence (© 2023). Any distribution of this work must maintain attribution to the author(s), title of the work, publisher, and DOI

19th Int. Conf. Accel. Large Exp. Phys. Control Syst.
ICALEPCS2023, Cape Town, South Africa
JACoW Publishing
ISBN: 978-3-95450-238-7
ISSN: 2226-0358
doi:10.18429/JACoW-ICALEPCS2023-THPDP101

Content from this work may be used under the terms of the CC BY 4.0 licence (© 2023). Any distribution of this work must maintain attribution to the author(s), title of the work, publisher, and DOI

19th Int. Conf. Accel. Large Exp. Phys. Control Syst.
ICALEPCS2023, Cape Town, South Africa
JACoW Publishing
ISBN: 978-3-95450-238-7
ISSN: 2226-0358
doi:10.18429/JACoW-ICALEPCS2023-THPDP101

The ALPS experiment, which stretches a total length of250 metres, is looking for a particularly light type of newelementary particle.
Figure 5 illustrates the fundamental concept of photonaxion and axion-photon conversion within ALPS II,
employing Feynman diagrams.

CONCLUSION
The goal is to make data easily accessible for analysis,
with a well-defined HDF5 format structure to select allneeded data by using a graphical tool for selecting
dedicated data. The present idea and partial
implementation indicate that the focus will no longer be on
cumbersome programming to extract data. Instead, theprimary focus will be on data analysis. This way, valuable
time and manpower can be saved or used more effectively.
We expect to have a first functional product by the endof 2023.

ACKNOWLEGEMENTS
Figure 5: Feynman diagrams of the photon-axion andaxion-photon coupling in ALPS II.
On the left-hand side, we observe a photon (γ) traversing
a robust magnetic field (B) and undergoing conversion into
an axion (a), which can subsequently pass through thelight-tight barrier. The right portion of the schematic
depicts the inverse process: the axion (a) encountering astrong magnetic field and undergoing reconversion into aphoton.
Using twenty-four recycled superconducting magnets
from the HERA 0 accelerator (Figure 6), an intense laser
beam, precision interferometry and highly sensitive
detectors are the heart of ALPS.

This publication was supported within Hub Matter at theHelmholtz-Zentrum Berlin by the Helmholtz Metadata
Collaboration (HMC), an incubator-platform of theHelmholtz Association within the framework of theInformation and Data Science strategic initiative.

REFERENCES[1] The HDF Group 2006,
https://www.hdfgroup.org/solutions/hdf5[2] DOOCS Homepage, https://doocs.desy.de[3] Aaron D. Spector for the ALPS Collaboration, “Approaching
the first any light particle search II science run”, Deutsches
Elektronen Synchrotron DESY, Hamburg, Germany, Apr.
2023.
doi:10.21468/SciPostPhysProc.12.039,
https://inspirehep.net/literature/2674982[4] HERA,
https://en.wikipedia.org/wiki/HERA_(particle_accelerator)

Figure 6: Inside the HERA tunnel.

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