# DATA DESCRIPTION AND COLLECTION OR RE-USE OF EXISTING DATA

Steunou Nathalie

► To cite this version:

Steunou Nathalie. DATA DESCRIPTION AND COLLECTION OR RE-USE OF EXISTING DATA. Institut Lavoisier de Versailles; Fondation des Sciences du patrimoine. 2025. hal-05328652

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https://hal.science/hal-05328652v1

Submitted on 23 Oct 2025

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# 1. DATA DESCRIPTION AND COLLECTION OR RE-USE OF EXISTING DATA

## 1a. How will new data be collected or produced and/or how will existing data be re-used?

According to the context of the project entitled Capture de composés Organiques volatils (COV) par des matériaux hyBRides poreux de type MOFs: Application liée à la conservation des momies et à la pollution de l'air dans les musées (COBRA), our first task was to synthesize nanoscale Metal Organic Frameworks (MOFs). The MOFs were synthesized using the reflux method, solvothermal method, and microwave-assisted procedure. These tasks were performed at Institut Lavoisier de Versailles (ILV), UVSQ, Université Paris Saclay. During the synthesis of materials, the following instruments has been used,

* VWR VMS-A heater and stirrer were used for the reflux method.

* Sigma (model 3-18 KS) centrifuge were used for collection of MOFs in case of all the protocols.

* Heraeus (Function Time) oven were used for both drying of the material and solvothermal method.

* Mars 5, CEM microwave was used for microwave assisted synthesis. Synergy Prep software was used to operate microwave.

The second task of this project was, characterization of the synthesized MOFs. Each new MOF material was designated by a code (For example, SDXXX (SD is an abbreviation of the user's name)) and was used for all analyses.

After the synthesis of the materials, they were primarily characterized by five basic techniques: powder X-Ray diffraction (PXRD), Fourier transform infra-red (FT-IR), Thermogravimetric analysis (TGA), Nitrogen Porosimetry and dynamic light scattering (DLS). The names of the instruments and software(s) used for the data recording for each method of characterization are as follows;

<table><thead><tr><td>Characterization Techniques</td><td>Name of the instrument</td><td>Software used to record the data</td></tr></thead><tbody><tr><td>Powder X-Ray Diffraction (PXRD)</td><td>Siemens D5000 Diffractometer</td><td>XRD Commander</td></tr><tr><td>Fourier Transform Infra-Red (FT-IR)</td><td>Thermo Scientific Nicolet 6700 FT-IR</td><td>OMNIC</td></tr><tr><td>Thermo gravimetric analysis (TGA)</td><td>Mettler Toledo Thermal Analysis</td><td>TGA DSC 3+</td></tr><tr><td>Dynamic Light Scattering (DLS)</td><td>Malvern nano ZS</td><td>DTS nano</td></tr><tr><td>Nitrogen Porosimetry</td><td>Micromeritics Tristar II Plus</td><td>Tristar II Plus</td></tr></tbody></table>

The third task was to use the synthesized MOFs for the capture of volatile organic compounds (VOCs) inside a showcase of a museum. This task was performed at Centre de Recherche et de Réservation des Musées de France(C2RMF), Paris. The Air tightness, real time reading of climate data, total concentrations of VOCs was using different instruments. After that the adsorption capacity of the materials was evaluated by measuring the concentration of VOCs.

* The air tightness of the showcase was measured using CO₂ as tracer gas and the concentration of the gas will be measured in Vaisala MI170 instrument for a week.

* The real-time reading of climate data was monitored in the same showcase using Hanwell ML2000s instrument for 2-3 days.

* The total concentrations of VOCs was quantified by using PID from RAE (Lamp 10.6 eV)

* The instrument that was used for the quantification of VOC is gas chromatography. This was measured after pyrolysis of the MOF materials at the boiling point of the VOCs concerned.

After recording the data from the respective instruments, the "raw data" was converted to readable file using some definite software(s). The readable file, which consists of several mathematical numerical values organized in the columns and rows, was represented as graph. To convert the numerical values into the graph Origin 2018 and Origin 8 software(s) was used as our primary choice. Sometimes Microsoft Excel was also be used to plot a curve.
We will use the same methodology as the one used for previously acquired data.
The data provenance is provided in the laboratory notebook of Sanchari Dasgupta.

1b. What data (for example the kind, formats, and volumes), will be collected or produced?

The detailed methodology of the material preparation was written in a laboratory notebook (Cahier de laboratoire) given by the institute and was returned to Prof. Nathalie Steunou after the project completion. Then the materials were characterized using several techniques as discussed in the previous section. The instrument-generated data of each characterization was stored in the respective computers attached to them. To use the data, we converted them to a readable file, and this readable file was transformed to an origin file or excel file. These data was stored for long-term use and shared with partners. One article is under preparation.

The data was encoded with the same name used during the synthesis of materials.

The format of the data for the characterization which we obtained from several instruments are as follows:

<table><thead><tr><td>Characterization Techniques</td><td>Name of the instrument</td><td>Filename extension used for storage in instrument's computer</td><td>Filename extension used for storage in user's computer</td></tr></thead><tbody><tr><td>Powder X-Ray Diffraction (PXRD)</td><td>Siemens D5000 Diffractometer</td><td>.raw file or .xy file</td><td>.opj file or .opju file</td></tr><tr><td>Fourier Transform Infra-Red (FT-IR)</td><td>Thermo Scientific Nicolet 6700 FT-IR</td><td>.spa file or .csv file</td><td>.opj file or .opju file</td></tr><tr><td>Thermo gravimetric analysis (TGA)</td><td>Mettler Toledo Thermal Analysis</td><td>.txt file</td><td>.opj file or .opju file</td></tr><tr><td>Dynamic Light Scattering (DLS)</td><td>Malvern nano ZS</td><td>.dts file or .xlx file</td><td>.opj file or .opju file</td></tr><tr><td>Nitrogen Prosimetry</td><td>Micromeritics Tristar II Plus</td><td>.SMP file</td><td>.opj file or .opju file and .PDF file</td></tr></tbody></table>

The procedure of the conversion of data in several formats or the file extensions has been described here.

1. Powder X-Ray diffraction (PXRD): The data obtained from instrument was .raw file and we converted it to .xy file by diffract.eva v 5.2 software. This .xy file was converted to either .opj file or .opju file using origin software.

2. Fourier Transform Infra-Red (FT-IR): We saved the FT-IR data both as .spa file and .csv file in the instrument computer using OMNIC software. We converted it to .opj or .opju file using .csv file in origin software.

3. Thermogravimetric analysis (TGA): The TGA data we obtained from instrument computer was .txt file. We used directly this file to origin software to convert it to .opj or .opju file.

4. Dynamic Light Scattering (DLS): The data we obtain was .dts file and with the help of dts nano software we converted the data as .doc or .xlx file. Then converted it to .opj or .opju file.

5. Nitrogen Prosimetry: The .SMP file which we get from the instrument was converted to .PDF file and .xlx file using Tristar plus II software. Then it was converted to .opj or .opju file.

For the experiments which was performed in C2RMF, we got Microsoft excel (.xlx file) file from our collaborators. These files will be used for future analysis.

The synthesis and characterization techniques were often represented in Microsoft PowerPoint as .pptx format. To draw the figures during this presentation we used chemdraw 15 software and the files were designated as .cdx file. This .cdx file can easily be exported to Microsoft PowerPoint. The main reason of using this format was, it can be used in different operating system (OS) of Computers. For example, the most widespread OS are Windows (several versions) and Mac OS. So, for the benefit of all the partners involved in this project and for later use this general software will be used.

To finalize the data of characterization, the most acceptable format was .opj or .opju format. The .opj format was most suitable because it can be accessed at different version of origin. The other advantages of using origin was as follows
I. The files can be easily exported to Microsoft applications (word and power point).

II. They can be converted to image file (.tiff file, .jpg file or .png file) by simple action.

III. They can also be used as .opj file in Microsoft word during writing reports or articles.

The format in which the data will be preserved for long time is as follows;

I. .docx

II. .xlsx

III. .pptx

IV. .opj/.opju

The exact storage space for the data is as follows,

<table><thead><tr><td>Characterization Techniques</td><td>Storage Space in Kb</td></tr></thead><tbody><tr><td>Powder X-Ray Diffraction (PXRD)</td><td>255</td></tr><tr><td>Fourier Transform Infra-Red (FT-IR)</td><td>125</td></tr><tr><td>Thermo gravimetric analysis (TGA)</td><td>1733</td></tr><tr><td>Dynamic Light Scattering (DLS)</td><td>229</td></tr><tr><td>Nitrogen Porosimetry</td><td>616</td></tr></tbody></table>

## 2. DOCUMENTATION AND DATA QUALITY

2a. What metadata and documentation (for example the methodology of data collection and way of organising data) will accompany the data?

The documentation of the data was divided into several steps,

**Step 1:** The synthetic methodology of the material preparation was written in laboratory notebook. Each material was be encoded with name SDXXX (SD is abbreviation of user's name). This name was used for the characterization and application of the materials.

**Step 2:** The data was characterized using the experimental conditions which was selected in the instrument computer. It was very important to record the exact experimental conditions used for each characterization techniques to ease the reproduction of the data.

i. For Powder X-Ray diffraction measurement, a single parameter file was used for all measurements. This was stored in the instrument computer.

ii. For FT-IR measurement the default settings was used.

iii. For TGA also the parameters were also stored in the computer.

iv. The parameters of the DLS measurement were saved in instrument computer.

v. The same was applicable for Nitrogen porosimetry also.

After optimization of the protocols, the best experimental conditions was written down in the laboratory notebooks.

**Step 3:** In the computers of the instruments the data was saved using this name. After collecting all the data of characterizations, they were stored in a folder with the same name in user's computer. All the experimental results from both ILV and C2RMF were stored in that folder. It will be easier for others to find this data.

**Step 4:** To minimize the probability of losing the data we stored this data to another device i.e. hard disk and in other computer of ILV.

**Step 5:** After gathering all the data they were finalized using the software(s) such as Origin and Microsoft Excel and they was saved in compatible mode. Therefore, they could be easily accessed to any operating system.

At the end of this project all the data and notebook were given to Professor Nathalie Steunou.

2b. What data quality control measures will be used?

It is very important to maintain the consistency of the scientific results.
Regarding the methodology of the material preparation at ILV, we changed several parameters during synthesis to optimize the materials (purity, properties...). The materials (obtained from different protocols) were characterized by standard techniques and these characterization data were compared with previously reported data (from precedent works in the laboratory or from literature). For reproduction of materials, we selected the synthetic protocol in which the obtained material has the most fitted data. The synthesis and characterization of an optimized material will be performed at least three times to evaluate the reproducibility of the data. A few equipment are required as well as calibration experiments (PXRD, N2 porosmietry...) and this will be performed regularly by the permanent researcher in charge of the equipment.

Concerning the experiments at C2RMF which involve extensive physicochemical experiments, we have to be precise. A few equipment are also required also calibration experiments (gas chromatography...). All the experiments were performed three times as decided by our collaborators. The average values of the measurements were taken into consideration for the valorization of data.

### 3. STORAGE AND BACKUP DURING THE RESEARCH PROCESS

3a. How will data and metadata be stored and backed up during the research?

The data was stored at first to the instrument computer. Then it was transferred to the user's computer and an external hard disk. They were backed up instantly as soon as we receive the data.

3b. How will data security and protection of sensitive data be taken care during the research

The data was stored in different computers and individual hard disks.

Since ILV is now under ZRR, we need to pay attention in the safety of storing and diffusing the data. Moreover, we respected the privacy policy of host institute. The raw data was not spread outside the institute. The readable data was collected by the user(s) and shared with the supervisor.

To discuss the results with our collaborators we presented all the results in PowerPoint and we mostly shared this file with the collaborators. The main data were stored in computers of ILV.

Before starting the project, I signed an agreement **Accord de confidentialité** which states that I will be secretive towards the data and documents of the project. To respect this commitment, I protected all the data and I did not diffuse them to others. I shared them with my collaborators of COBRA during scientific discussion only.

### 4. LEGAL AND ETHICAL REQUIREMENTS, CODE OF CONDUCT

4a. If personal data are processed, how will compliance with legislation on personal data and on security be ensured?

During this project no personal data was processed.

4b. How will other legal issues, such as intellectual property rights and ownership, be managed? What legislation is applicable?

According to **Accord de confidentialité** the data collected belong to the different institutions involved in COBRA (ILV, C2RMF) and they are not openly accessible. We followed the principles adopted by the CNRS in such a research collaboration with respect to the development and protection of results: these principles were (i) the ownership of results to partners who have contributed to their production (ii) the preservation of researcher publication rights. We will obey all the rights of control in sharing the data with the partners of the project.

We did not decide yet the usage of a third-party data. The **scientific impact of the work** developed in this project was expected to be substantial. The dissemination of the results was performed through
presentations at conferences such as Euro MOF 2023, E-MRS 2024 and publications and this was be
performed with the agreement of all partners of COBRA.

4c. What ethical issues and codes of conduct are there, and how will they be taken into account?

We followed the principles adopted by the CNRS in such a research collaboration with respect to the
development and protection of results

5. DATA SHARING AND LONG-TERM PRESERVATION

5a. How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons?

At the end of the project, the data will be safely stored on the computers and hard disks of the institutions involved in COBRA (ILV, C2RMF). They will be also stored and accessible through a CNRS database (My CoRe). First, data will be shared only between partners of COBRA and then they were disseminated through publications and patents. Once the results are exploited through publications and/or patents, they can also be diffused to other scientific communities or end-users.

5b. How will data for preservation be selected, and where data will be preserved long-term (for example a data repository or archive)?

As previously explained, the data were stored on the computer or external disks of the institutions involved in COBRA (ILV, C2RMF) and in My CoRe Cloud.

5c. What methods or software tools are needed to access and use data?

All the data was converted to readable file as we said in section 1b. Four simple software(s) was used for future
handling of the data, (i) Origin (The data was processed in such a way that they can be accessed by any version), (ii)
Microsoft Excel, (iii) Microsoft PowerPoint, (iv) Microsoft Word

5d. How will the application of a unique and persistent identifier (such as a Digital Object Identifier (DOI)) to each data set be ensured?

The data cannot be reused in other context before publication of those data in an article format or as a patent. After
publication we will get Digital Object Identifier (DOI) and then the data can be used again.

6. DATA MANAGEMENT RESPONSIBILITIES AND RESOURCES

6a. Who (for example role, position, and institution) will be responsible for data management (i.e. the data steward)?

Since the experiments were performed in two institutions, the data was stored in two different places. The responsible
for the data management is as follows;

<table>
   <thead>
    <tr>
     <td>
      Institution
     </td>
     <td>
      Responsible Person
     </td>
     <td>
      Role in COBRA
     </td>
     <td>
      Role for data management
     </td>
    </tr>
   </thead>
   <tbody>
    <tr>
     <td>
      ILV, UVSQ
     </td>
     <td>
      Nathalie STEUNOU
     </td>
     <td>
      Project Supervisor
     </td>
     <td>
      Responsible of the DMP (implementing and regular update) and for the data storage, curation and archiving at ILV
     </td>
    </tr>
    <tr>
     <td>
      ILV, UVSQ
     </td>
     <td>
      Sanchari DASGUPTA
     </td>
     <td>
      Post Doctorate Researcher
     </td>
     <td>
      Management of data acquisition, update of the DMP and sharing of data through the MyCore
     </td>
    </tr>
   </tbody>
  </table>
<table><tr><td></td><td></td><td></td><td>CNRS database</td></tr><tr><td>C2RMF</td><td>Agnès LATTUATI-DERIEUX</td><td>Project Co-Supervisor</td><td>Responsible of the data storage and curation at C2RMF</td></tr><tr><td>C2RMF</td><td>Juliette RÉMI</td><td>Project Collaborator</td><td>Responsible of the data archiving at C2RMF</td></tr></table>

6b. What resources (for example financial and time) will be dedicated to data management and ensuring that data will be FAIR (Findable, Accessible, Interoperable, Re-usable)?

Off course, no financial resource is specifically dedicated to this task. The time allocated to this task is huge and cannot be quantified. It can take at least half-day per a week for acquisition and management of data.