The ultraconserved intersubunit ribosome assembly factor (InsuRAF)

Keywords: methodology, software, primary formats & estimated volumes Data type Methodology, instrument Software, database or repository Deposited protein sequence, conservation, phylogenetic distribution, domain architecture (text, image, code) Data retrieval, analysis & visualisation InterPro, UniProt, PFAM, NCBI BLAST, NCBI Assembly, Python FAS, TXT, JPEG, PNG, Data retrieval, analysis & visualisation neXtProt, PeptideAtlas, ProteomeXchang e Consortium, Scaffold mzML, TXT, TSV, XLSX, JPEG

o Minor editorial fixes are performed.

1. Data description & collection or re-use of existing data 1a. What data (for example the kind, formats, & volumes), will be collected or produced?

). In the majority of cases, the type of the instrument employed to collect data dictates the proprietary software and the format in which the data are first registered and undergo primary analysis. Similarly, databases and on-line analysis tools impose built-in search engines and retrieval options. In addition to these specific formats, storage, downstream manipulations, analysis, aggregation, and visualisation of the data will be performed in open or standard formats (TIF for most images, JPEG or PNG for gels and structure snapshots, AI and PDF for assembled images, DOCX for text documents, TXT for sequences and alignments, XLSX for spreadsheets, PDB for structures), wherever possible, as recommended in Turning FAIR into reality and Guide Pratique de la publication en ligne et de la réutilisation des données publiques ("Open data") elaborated by CNIL and CADA.

Table I. Data types,

o Table 1 is updated to reflect the actual types and volumes of data collected, produced or re-used in this project.

o Table 2 is updated to include a new column of the CER file: "Status".

o Table 3 is expanded to include new kinds of methods and their descriptors.

o Table 4, Plasmids now contains an additional series of columns "Sanger file 1, 2 etc" to directly link plasmid entries to their Sanger sequencing data.

o Table 4, Bacterial strains now has a more detailed Description section.

o Table 5 slightly modifies the structure of the lab protocol by proposing to directly reference specific experiment IDs that describe cases of successful or unsuccessful implementation of the protocol.

o Since certain datasets have been produced in several geographical locations, Table 6 now includes geographical coverage in the "Coverage" section of the standard metadata file.

o Section 2 now implements the principle of separation between primary data and analysis outputs.

o Section 2a now includes a description of EnzymeML metadata supporting enzymatic assay datasets.

o The list of persons authorised to curate and modify research resources and documentation (section 2a) has been updated.

o Section 2b incorporates further quality control measures related to equipment and certain field-specific data types.

o Image Data Resource (IDR) and Bioimage Archive (BIA) are identified as trusted repositories for microscopy data published in the frame of the InsuRAF project. REMBI is identified as an appropriate metadata format for these data. Zenodo and Research Data Gouv are identified as trusted generalist repositories for other kinds of data. The corresponding sections have been updated accordingly. By contrast, as no important structural data could be generated in this project, wwPDB policies are reduced only to cover what concerns the re-use of deposited datasets.

o Section 3b now includes security measures concerning lab books. 1b. How will new data be collected or produced &/or how will existing data be re-used?

The methodologies, databases and software employed to collect, produce or re-use the data are specified in Table 1. The implemented techniques rely on a maintained system of in-house protocols, research resources, instruments and software either directly available in the host laboratory or reachable via collaborations and TGIR (Synchrotron SOLEIL). Data re-use concerns both publicly available deposited and/or published data and previously collected in-house data and samples. In the collection, production, and re-use of data, we follow general archiving principles described in La vie d'une donnée au regard des réglementations "CRPA", "RGPD" et "Patrimoine".

The provenance of re-used data is documented with the help of the associated persistent identifiers (e.g. UniProt and InterPro entries, PDB ID, PXD, RefSeq ID, article reference/PMID, HAL ID, DOI). Some of the repositories used in this project (e.g. ProteomeXchange, wwPDB) have established versioning pipelines with rich provenance metadata enabling reconstruction of detailed lifelines of the deposited data. In the case of data from continuously updated databases (e.g., phylogenetic distributions, BLAST, PDB searches), the filters and the date of the search are additionally specified. For predictions, parameters, filters, and on-line software versioning information are provided. The provenance of collected and produced data is documented in the form of metadata, lab book entries, and the Central Experiment Registry (CER, see section 2 2). These data are matched with those of the corresponding lab books and metadata files, which obligatorily use the same identifiers to ensure complete cross-referencing.

File names follow pre-established conventions and are built as follows:

NNE#####_yyyymmdd_MMMMMMMM.extension
where NNE##### is the number of the experiment, yyyymmdd is the date (in the ISO 8601 format) when the file was generated, MMMMMMMM is a method-specific descriptor, as listed in Table 3. This name may be followed by a letter suffix ("a", "b", "c" etc) if it concerns a modified version of the initial file, or by a disambiguation number suffix ("1", "2", "3" etc) if the same type of data was acquired on the same day and needs to be distinguished from an already existing but unrelated file. Exceptions from this file naming system exist: files produced by some external services and collaborators retain their original names for the reasons of traceability and communication. In this case, a normal metadata file is nevertheless created to capture their provenance and experimental details. The data obtained at

Status

The current status of the dataset. Has three possible values: "Active", "Archived", "Suppressed". InsuRAF -Data Management Plan Version 3 -December 26, 2023 synchrotron SOLEIL are subject to a specific SOLEIL Data management policy (DSI-DU-P-0056; October 2, 2018) covering standardised metadata formats and vocabulary, specific data formats, and the software required for their manipulation provided by SOLEIL, and attribution of permanent unique identifiers to experiments and datasets (see section 5d). FAIR research (version 5, May 16, 2022), we implement the principle of separation of primary and processed datasets. Primary research data are stored in CER folders as read-only original files. By contrast, the corresponding output files -that build on the primary or re-used data, but are not themselves primary data -are created and stored as separate digital objects (files) in dedicated "analysis" subfolders (versioned as "Analysis01", "Analysis02" etc) within each experiment folder. These "analysis" files are diverse in format (text, spreadsheet, annotated image, PyMol session etc). They cross-reference the original data and research resources they are based on using the in-house CER taxonomy (for internally produced data) or database-specific persistent identifiers (for publicly deposited data -both internally and externally produced). The "analysis" subfolders also capture, in as much detail as possible, all modifications or filtering/censoring applied to data, analysis pipelines, software versions and settings -either directly within their body (documentation) or by means of associated README files.

CER and the file naming system are rooted in the research resource taxonomy which includes unique identifiers for protocols, cell lines, bacterial strains, plasmids, DNA oligonucleotides, antibodies, and synthetic nucleic acids. Whereas the latter two categories almost invariably use manufacturer-provided references (unless the resource in question was specifically created for exclusive in-house use), the remaining in-house resources follow the conventional naming and numbering system: cell lines -SAL###, bacterial strains -SAB####, plasmids -pSAP####, DNA oligonucleotides -SAO#####, which corresponds to their physical organisation in storage cryo-boxes. Each kind of resource is catalogued in a dedicated spreadsheet which ensures cross-referencing to other resource types (Table 4). In addition to built-in metadata associated with instrument-specific primary files (including such information as date, instrument, and acquisition settings), a dedicated TXT metadata file accompanies each dataset. The metadata file name is built following these conventions:

NNE#####_DublinCore_metadata.txt
where NNE##### is the number of the experiment in CER. An experiment may have several associated datasets and the corresponding number of metadata files which, in this case, assume a suffix "_1", "_2", "_3" etc. When the experiment is finished and all associated data have been collected, it is archived, and the metadata file name is extended with "_archived". In this state, it is not subject to modification any more (read-only). (At this stage, however, it is still considered as 'intermediate data' not necessarily deemed for long-storage preservation -see section 5a.)

A standard metadata file is organised in accordance with the Dublin Core format and includes 15 generic entries ( CNRS has recently begun to deploy, on voluntary bases and at the scale of entire research units, digital lab books (CNRS Research data plan, November 2020). This tool would permit linking together CERs, data, metadata, protocols, and research resource IDs, and their sharing between the participants of the project would become even more straightforward. Although, for the time being, UMR7156-GMGM made choice not to enrol, we foresee that future introduction of digital lab books may require reshaping of the metadata system to avoid redundancy between them (since the digital lab book is expected to contain most of the information currently stored within metadata files, even though in a less formal way). However, the essential external function of metadata to make data FAIR (Turning FAIR into reality.

Final report and qction plan from the European Commission Expert Group on FAIR data, November 2018) and the necessity to be able to share intermediate data selectively, without disclosing other, unrelated and/or sensitive intermediate data impose the metadata as the primary entities which necessarily have to be complete and self-sufficient. In this perspective, the lab book retains the roles of:

(i) the connecting node between various data, metadata, protocols, and research resources that organises them in experiments and ensures crossreferencing; InsuRAF -Data Management Plan Version 3 -December 26, 2023

(ii) the contextualisation tool that explains the place of data and processes in the research; (iii) the space for data post-analysis (e.g., plotting, display of adjusted images to visualise specific features, association of non-data objects and links etc) as well as for free-style interpretation and hypotheses.

Finally, the present Data Management Plan (DMP) can be considered as another piece of metadata describing the entire organisation of the data, metadata, protocols, and research resources produced and/or enacted in the frame of the InsuRAF project. It follows the outline and requirements elaborated in the Science Europe Practical guide to the International alignment of research data management (January 2021), further detailed in Additional guidance to the Science Europe DMP assessment rubric, and is subject to publication on Zenodo under the CC BY Attribution 4.0 International license.

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

Three cases should be distinguished: collected, re-used, and produced data.

Since all the methods employed to collect data in this project have been extensively characterised and widely used by the scientific community, their quality can be evaluated by compliance with field standards. Those include technical, design, reproducibility, documentation, and digital measures and criteria (Table 7). In addition to these general criteria, further quality checks (implemented in specific metadata and data presentation modes) are applied to select types of data with community-endorsed "minimal information" requirements (see Minimum Information for Biological and Biomedical Investigations) and "best-practice" guidelines, such as microscopy (Community-developed checklists for publishing images and image analyses), qPCR (MIQE), molecular interaction (MIMIx) or enzymatic activity (STRENDA) data.

The main task of data quality control falls first to the experimenter, who ensures the compliance of the protocol and the experimental outcome with the established standards, documents and interprets the experiment (in the lab book and CER), and then to the principal investigator (Alexandre SMIRNOV), who reviews the protocol, data and metadata and re-evaluates their compliance with the community standards and the validity of the interpretation. The Lab Manager (Christelle GRUFFAZ) ensures the identity, digital and physical maintenance of the associated research resources (reagents, protocols, cell lines, strains, plasmids, oligonucleotides, synthetic RNAs, antibodies) and equipment (pipettes, instruments). The experimenter ensures the identity and maintenance of collected data and metadata. InsuRAF -Data Management Plan Version 3 -December 26, 2023 Produced data (i.e., those resulting from analysis of collected or re-used data) should be themselves based on high-quality data, as outlined above, and additionally satisfy a set of specific criteria. Those include: a) unequivocal association with the corresponding primary data (by including raw data and referring to their unique identifiers or databases), b) metadata with clear information about the date and the analysis protocol (including definitions, prediction parameters, information about binning, thresholding, normalisation, transformation, statistical analyses, software etc) captured as within-file documentation or in a separate README file, c) respecting field conventions for each kind of analysis or justification of deviations from them, d) compliance with the assumptions and requirements of adopted statistical analyses and visualisation modes, e) sample inclusion and exclusion criteria, f) portable and convertible format permitting facile re-run or alternative visualisation with desktop or online tools, g) proper organisation in an "analysis" subfolder with a transparent structure that captures the processing workflow. InsuRAF -Data Management Plan Version 3 -December 26, 2023

Zenodo General Policies (version 1.0) recognise the ownership for the parties prior to submission and do not imply any transfer of property rights.

Recherche Data Gouv uses the open-access etalab2.0 license by default, but permits the use alternative/additional licenses, including CC BY. etalab2.0 is designed to be compatible with CC BY.

There are no restrictions on the re-use of third-party data deposited to public databases within the perimeter and at the scale foreseen in this study (see

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

Not applicable (no human or animal subjects, communities, their cultural and/or genetic resources, personal or other ethically sensitive data were used in the study).

Data sharing & long-term preservation

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

At this stage of the project, when most intermediate data have already been obtained and partially published, and the quality and value of each piece of data can be evaluated with more confidence and in a broader context, the selection of data for ultimate archiving can be initiated. To this end, the intermediate data are parsed in four groups:

1) actively used data, independently of their quality, associated with or potentially important for ongoing or future research tasks within the InsuRAF project or for other ongoing research projects (e.g. EURICA); 2) high-quality published or ready-to-publish data; InsuRAF -Data Management Plan Version 3 -December 26, 2023

3) other high-quality data which are not expected to be used in the foreseeable future but are required to fully document the research process and, if needed, support published data or priority claims; 4) low-quality data without significant scientific value which are not expected to be used in the foreseeable future.

In addition to the quality criteria described in section 2b, curation of datasets is carried out in accordance with 10 things for Curating Reproducible and FAIR Research. The destiny of each category of data is different.

The Group 1 data are not subject to archiving and continue to be managed, as described in section 3. SOLEIL acts as custodian for all raw data and associated metadata collected at the synchrotron. It ensures long-term storage and curation of the data and the associated metadata. These data and metadata follow the SOLEIL Data management policy (DSI-DU-P-0056; October 2, 2018) for formatting, storage and sharing. SOLEIL does not curate reduced or processed data and the associated metadata. SOLEIL stores but does not curate results issued from analyses performed on raw data and metadata using SOLEIL means. Foreseeable uses of the data include but are not limited to re-analysis, benchmarking, and algorithm training.

Data submission guidelines for the ProteomeXchange Consortium (version 3.0.1; October 13, 2019) regulate the deposition of mass spectrometry data. The ProteomeXchange Consortium similarly permits withdrawing unreleased datasets by the authors' decision. The withdrawn datasets will still be present in the list of unreleased entries, and their internal copy will be kept by ProteomeXchange Consortium but will remain inaccessible to external users. Released datasets associated with published research cannot be withdrawn (unless there are exceptional circumstances, such as major errors, retraction of the corresponding article, or violation of property rights). Preprints are not considered publications under the ProteomeXchange Consortium policies, and the repository does not encourage releasing datasets prior the acceptance of the final paper for publication. PRIDE (as part of the ProteomeXchange Consortium) in its General guidelines for submitted datasets (version 1.0, May 2022) aligns with these policies and engages to maintain all published datasets publicly accessible as part of scientific record. The PRIDE team InsuRAF -Data Management Plan Version 3 -December 26, 2023 also offers the creation of additional metadata (e.g. Sample and Data Relationship Files, mzTab and mzIdentML files) to facilitate the re-use of deposited datasets.

BioImage Archive (BIA) functions as a permanent public repository of imaging data associated with peer-reviewed publications or of value beyond a single experiment.

It also provides archiving services for other bioimaging databases, e.g. IDR. It supports FAIR Sharing and implements REMBI guidelines for FAIR data. BioImage Archive Policies (version 1.1) provide general guidelines about deposition of datasets. BIA allows for up to 3 months of transient storage for uploaded data, after which the dataset is either formally submitted for permanent deposition or deleted. The data can be released either right away or upon article publication (and in any case no later than 2 years after submission). All deposited data are permanently accessible for scientific record. They can be amended or updated, or even removed from visibility by search (in case of an erroneous submission). BIA reserves the right to obsolete datasets due to integrity, correctness, ownership, or provenance issues (e.g. article retraction or other official decision of integrity bodies).

In either case, the data in question will nevertheless remain accessible via their PID.

The quality and accuracy of the deposited data are the responsibility of the authors.

Image Data Resource (IDR) is a more specialised repository focused on reference data from published (or only submitted) studies with particularly rich metadata to enable their re-use by third parties (Williams et al., Nat Methods, 2017). IDR Submission Guidelines (v1.0, March 2017) require the datasets to be complete and integrated with other databases and biomolecular resources via PIDs. IDR supports a wide variety of proprietary and open file formats (with the preference for the latter), including those implemented in the InsuRAF project (section 1a).

BIA scope and submission to related resources explains the difference in scope between BioImage Archive and other, more specialised repositories, such as IDR, thus guiding the choice of repository for different kinds of imaging data. BIA and IDR actually overlap on this point and work together to coordinate and link submissions between the two repositories; more specialised IDR deposits are imported into BIA. BIA plans to provide a possibility of parallel submission to both the databases.

Zenodo permits the deposition of any kinds of research data in any format under any access conditions. Zenodo does not perform quality checks, does not guarantee usability or understandability of deposited data. This repository stores metadata in the JSON format, with the possibility of export to other widely used formats, e.g. Dublin Core, via OAI-PMH. Submitters themselves specify the desired license in the process of submission, which determines use and re-use possibilities. Metadata are licensed under the CC0 license. Zenodo General Policies (version 1.0) reserve the right to remove datasets and revoke their DOI in cases where the datasets in question do not fall into the scope of the repository or violate its terms of use. Under exceptional circumstances, the submitter can request withdrawal of one of his datasets, which requires full justification. If the withdrawal is granted, the dataset page is replaced by a "tombstone" page, but the original DOI and URL are retained.

Finally, the recently created general-use French national platform for research data, Recherche Data Gouv, permits deposition of any types of data for which no trustworthy repositories currently exist as well as cataloguing/linking to data deposited in other trusted national or international repositories. The deposited data must be complete and accompanied by structured metadata. Zenodo versions all deposited documents and assigns each new revision a unique DOI. For example, the two previous versions of this DMP can be here (doi: 10.5281/zenodo.5767156) and here (doi: 10.5281/zenodo.5776148).

Recherche Data Gouv its own versioning policy that permits adding, removing or deleting files, adding or modifying metadata, and changing license terms. Any change results in republication of the dataset as a version under the same DOI (DOIs are only linked to the latest version of the dataset). The repository distinguishes minor (labelled 1.1, 1.2 etc) and major revisions (labelled as 2.0, 3.0 etc). The latter option is used to accommodate any changes in files or citations.

The Group 3 data undergo archiving. They may be later re-used by the research team or collaborators and shared with third parties (members of the research community or governing bodies), following the modalities described in section 3b, for research purposes, or to ensure the integrity of the research record, or to support InsuRAF -Data Management Plan Version 3 -December 26, 2023 priority claims. Foreseeable uses of such data include but are not limited to publication, follow-up, replication or comparative studies, re-analysis, benchmarking, algorithm training. The expected volume of the collected and produced data (see Table 1) permits their long-term preservation on hard drives or in the Data Centre in house. Since no personal data were collected or are expected to be collected in this research, there is no legally imposed limit on the duration of data preservation.

The archiving procedure includes three components: (i) evaluation and, if needed, fixing of the quality and completeness of the dataset (see section 2b), (ii) copying and transferring the dataset in question to the archive hard drive and (iii) creation of the corresponding records management metadata. All archived data and the associated metadata are by default read-only. The archive hard drive is preserved in a separate location. The archived copy of the dataset is accompanied by a records management metadata file in a TXT format, based on the Dublin Core model and named according to the following conventions:

NNE#####_RM_metadata.txt
where NNE##### is the number of the archived experiment in CER (see section 2a). This file is organised as described in Table 9.

Another copy of the archived dataset continues to be preserved on the original hard drive but is moved to a dedicated folder "Archive"; it is not subject to backup any more. Its place in CER is taken by a read-only records management metadata file identical to the one in the archive, to enable localisation of the archived data and reconstitution of their record management. InsuRAF -Data Management Plan Version 3 -December 26, 2023 The Group 4 data are suppressed. The suppression procedure includes three components: (i) deleting the data in question from the corresponding CER folder while preserving all the metadata of the suppressed dataset, (ii) transferring the folder with the metadata to the archive, and (iii) creation of the corresponding records management metadata. The latter follows the Dublin Core model, as described in Table 10. InsuRAF -Data Management Plan Version 3 -December 26, 2023 As in the case of archived datasets, the place of the suppressed folder in CER is taken by a read-only records management metadata file identical to the one in the archive, to enable the localisation of the remaining metadata of the suppressed dataset and the reconstitution of their record management.

The sorting of intermediate data and the decision to eventually archive/suppress them will be taken on a monthly basis and will only concern the datasets (CER experiments) that have not been in use for at least one year. The decision to suppress a dataset must be systematically approved by a hierarchical authority (in this case, the Principal Investigator, Alexandre SMIRNOV).

Note a difference in the granularity of the suppression procedure between the Group 3 and the Group 4 data. Group 4 datasets are suppressed entirely, whereas individual files from Group 3 datasets may be suppressed prior archiving, following a similar suppression procedure, if they are damaged or devoid of scientific value, InsuRAF -Data Management Plan Version 3 -December 26, 2023 books and data arrays susceptible to become object of IPR can be shared with third parties upon request directly handled by the Principal Investigator (Alexandre SMIRNOV) upon consultation with collaborators and eventually SATT Conectus Alsace. Pursuing a patent constitutes a reason for which the relevant data may not be released until the patent is granted or rejected.

Prior to article publication, relevant datasets are deposited in dedicated repositories (see section 5a) and become discoverable by their unique identifiers (see section 5d) and key words through search engines. Upon publication (or, in some journals, prior to publication), they are rendered open-access (under the CC BY license, wherever possible) and follow the policies of the corresponding repositories.

The data, metadata and results obtained at the synchrotron SOLEIL are discoverable via a searchable on-line catalogue (restricted to registered users). The embargo period is defined in the SOLEIL Data management policy (DSI-DU-P-0056; October 2, 2018) as 3 years after the end of the beamtime (default), and cannot exceed 5 years. It can be shortened upon request from the Principal Investigator (e.g., if the corresponding results are published). Past this time, all the data and metadata are automatically rendered open-access under the CC BY licence. Access to the data during the embargo period is controlled by the Principal Investigator (Alexandre SMIRNOV) and by the Main Proposer (Benoît MASQUIDA). Additionally, §4.18 of the SOLEIL Data Management Policy grants SOLEIL access to all collected data and metadata for curation and sharing purposes.

In the case of the ProteomeXchange Consortium (Data submission guidelines for the ProteomeXchange Consortium, version 3.0.1; October 13, 2019), unreleased data are by default private (password-protected); access to them is controlled by the Principal Investigator (Alexandre SMIRNOV) and the Submitter. Access to unreleased data can be granted to third-parties upon consultation with collaborators. It is systematically granted to journals for the convenience of referees. Upon the publication of the original article, the corresponding datasets are immediately released under the CC0 licence without embargo (note, however, that ProteomeXchange Consortium envisages moving to the CC BY license as default). PRIDE (as part of the ProteomeXchange Consortium) in its General guidelines for submitted datasets (version 1.0, May 2022) aligns with these policies. Of note, regardless the choice of the CC0 license, PRIDE insists that users re-using a deposited dataset should give appropriate credit to the original authors/submitters by citing the dataset or the associated paper.

IDR Submission Guidelines (version 1.0) permit datasets to remain private over a defined period of time (typically until article publication) but require them to be released thereafter. Once deposited data have been validated, their publication takes at least 3 weeks and DOI minting another week. There is no opportunity to generate private access tokens for referees.

BioImage Archive Policies (version 1.1) do not allow for embargo to be placed on deposited datasets.

Datasets deposited to Recherche Data Gouv can be embargoed for up to 18 months. There is a possibility to create a private URL to enable access to unpublished datasets by referees.

Zenodo permits to reserve access to deposited data for indefinite time.

  InsuRAF -Data Management Plan Version 3 -December 26, 2023 0. What changed with respect to the Version 2 of this DMP o This DMP version is explicitly licensed under the CC BY 4.0 Attribution International license, enabling its free and widest re-use by the community.

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

  The overall organisation of research data follows RDA-endorsed recommendations (10 things for curatingreproducible and FAIR research, version 5, May 16, 2022). The research data organisation is embodied in the form of the Central Experiment Registry (CER) and the associated digital research infrastructure. CER is organised in folders assigned to each Creator. Each such folder contains subfolders corresponding to individual experiments and named "NNE#####", where NN are the Creator's initials and ##### is the number of the experiment (continuous numbering). Each CER folder also includes a Microsoft Excel spreadsheet (or CER sensu stricto) with a complete list of experiments for which the Creator is responsible. Each row of this spreadsheet corresponds to one experiment. The columns contain standardised information about experiments (Table

). InsuRAF -Data Management Plan Version 3 -December 26, 2023 2.

Table 2 . Central Experiment Registry (CER) columns

 2

	Experiment ID	Experiment identifier in the format NNE#####
	Participants	Initials of the person(s) directly contributing to the experiment
	Affiliations	Affiliations of the person(s)
	Started	Date of the beginning of the experiment
	Completed	Date of the completion of the experiment
	Description	Very short description/title of the experiment
	Associated files	Complete list of all files generated in the experiment
	Associated files	Additional columns (if the capacity of the previous cell happens to be
	2, 3 etc	insufficient to visualise all file names)

Table 3 . Some method-specific descriptors used in file naming Method Descriptors Interpretation

 3

	Gel	AGE_BEt	Agarose gel stained with BEt
	electrophoresis
		PAGE_Coomassie	Polyacrylamide gel stained with
			Coomassie
		PAGE_Stain-free	Stain-free polyacrylamide gel
		PAGE_Ag	Polyacrylamide gel stained with silver
		PAGE_Phos	Polyacrylamide gel visualised with
			PhosphorImager
	Blotting	NB_SAO#####	Northern blot with oligonucleotide
			SAO##### as probe
		WB_White	Western blot white light image
		WB_Abref_##s	Western blot with primary antibody Abref
			exposed for ## s; Abref = unique
			antibody identifier (reference number)
		WB_Radio	Western blot visualised with
			PhosphorImager
	UV-VIS	Spectra	UV-VIS spectra report
	spectrum
	Sanger	Seq_pSAPnnnn_PPPP	Sanger sequencing of the plasmid
	sequencing		pSAP#### with the primer PPPP
	PCR	PCR_SAO#####_SAO##### PCR with primers SAO##### and
			SAO#####
	Quantification Quant	Spreadsheet with quantification data
	Structure	Structure	Secondary or tertiary structure of a
			molecule
	Sequence	Sequence	Annotated sequence of a gene, a
			transcript or a protein
	Analysis	Analysis	A free-form qualitative analysis including
			images, schemes, and other kinds of data
			that cannot be captured under the
			"Quant" category

Table 4 . Key research resource catalogues & their columns DNA oligonucleotides

 4

	Oligo ID	Oligonucleotide identifier SAO#####
	Created	Date of order

Sequence

Oligonucleotide sequence in the 5'-to-3' direction Description Intended uses of the oligonucleotide, its peculiarities (modification, restriction site, amplified or detected gene & organism etc) Notes Any useful information or observations InsuRAF -Data Management Plan Version 3 -December 26, 2023 Complete list of oligonucleotides (SAO#####) used to create the plasmid Sanger file 1, 2 etc A series of columns containing links to Sanger sequencing data of the corresponding plasmid Bacterial strains Strain Strain ID SAB#### Date created Date of the original DMSO/glycerol stock Species & strain Bacterial species & strain Genotype Genetic background with eventual mutations or modifications Plasmids Hosted plasmids pSAP#### (with an ordinary name if empty vector) Resistance All known resistances of the strain Description Intended use of the strain: "Primary stock" (genetically unmodified, usually lacking plasmids), "Storage strain" (for plasmid storage & isolation), "Expression strain" (for protein overexpression), "Constructed strain" (genetically modified in a specific way) Protocols (NNM###) are named by the Creator's initials (NN) and numbered (###). Their versions are labelled with letter suffixes ("a", "b", "c" etc). Protocols have an invariate structure, as outlined in Table 5. They necessarily cross-reference all related research resources. InsuRAF -Data Management Plan Version 3 -December 26, 2023

Table 5 . Protocol structure Entry Content

 5

	Title	Name of the protocol
	Date	Date of the last edit (excluding major modification, which normally
		requires versioning)
	Associated protocols	Any other protocols related to the present one
	Solutions & reagents	Complete list & compositions of buffers & chemicals required for the
		experiment
	Kits	Any kits required for the experiment (with links to manuals)
	Instruments & specific	Any instruments or consumables required for the experiment
	consumables

Biological materials

Organism, tissue, specific strain, cell lysate, or any other material directly used in the protocol Time estimate Minimal (with no facultative breaks used) and maximal (with all facultative breaks included) duration of the protocol Breaks Steps at which experimental manipulations may of have to be interrupted for more than 12 h Successful implementation Examples of strains, proteins, or other biological entities for which the protocol has already been successfully used in house, with references to specific experiments Unsuccessful implementation Examples of strains, proteins, or other biological entities for which the protocol failed in house (with brief notes & proposed alternatives), with references to specific experiments Protocol Step-by-step experimental guide

Table 6

 6

), eventually followed by the concluding tag #archived#. InsuRAF -Data Management Plan Version 3 -December 26, 2023

Table 6 . Metadata file organisation (for research data)

 6 Data Management Plan Version 3 -December 26, 2023 An additional metadata file is generated for enzymatic assays. It uses the EnzymeML macros template(Lauterbach & al., "EnzymeML: seamless data flow and modelling of enzymatic data", Nat Methods 2023) based on Systems Biology Markup Language (SBML). The metadata file name is built following these conventions:NNE#####_EnzymeML_metadata.xlsmwhere NNE##### is the number of the experiment in CER. Once the template is filled out, the file is saved as a regular .xlsx file, as recommended by the developers. The EnzymeML metadata and the associated infrastructure are designed to support the FAIR principles. The metadata are formatted in a way that directly enables downstream kinetic modelling in COPASI and data deposition in the EnzymeML Dataverse, SABIO-RK, or STRENDA DB repositories.

	Entry	Description
	1. Title	Short title of the experiment
	2. Creator	Person (name, ORCID) &/or institution who created the metadata file,
		usually the main experimenter
	3. Subject	Type of the experiment (method)
	4. Description Concise description of the experiment, including (i) relevant IDs of in-
		house research resources (cell lines, strains, plasmids, oligonucleotides,
		antibodies, protocols with eventual deviations), (ii) all generated files in
		the dataset & their descriptions (type of data, order & amount of samples,
		technical observations), (iii) any additional textual information which does
		not make part of a separate file (e.g., OD measurements, concentrations,
		qualitative remarks)
	5. Publisher	Université de Strasbourg
	6. Contributor Person(s) (names, ORCIDs) &/or institution(s) who directly contributed to
		the experiment
	7. Date	Date of the last modification
	8. Type	Nature of the data (e.g. gel scan, 3D model, UV absorbance spectrum)
	9. Format	Name of the folder & eventually subfolder(s) in which the data are
		classified
	10. Identifier	ID of the experiment & a complete list of the files & subfolders in the
		dataset
	11. Source	Primary or secondary (in the case of data re-use or re-analysis)
	12. Language	English
	13. Relation	IDs of all other experiments &/or data or metadata to which the present
		dataset is related in terms of deliverables, continuation, replication,
		modification, re-use, or re-analysis
	14. Coverage	Time period between the beginning of the dataset & its completion;
		geographical coverage (city, state)
	15. Rights	IPR Unistra

As an alternative metadata format, an MS PowerPoint file (PPT), containing the experimental image with detailed annotation and relevant information on the experimental design, is used by some collaborators. This file is named in the same way as the original file it refers to (see below), followed by "_annoté". InsuRAF -0; March 2017; BioImage Archive submission -Lab Guide). In particular, REMBI metadata will be created to accompany published microscopy datasets selected for deposition to BioImage Archive. The possibility of introducing other data type-specific FAIR-compatible metadata formats, approved by the corresponding communities, continues to be studied.

All the research resources are shared between the participants of the project via the protected Seafile cloud space hosted by the University of Strasbourg. They are retrievable by all participants of the project. They are curated and modified by authorised participants (Alexandre SMIRNOV, Christelle GRUFFAZ, Anna SMIRNOVA, Zhen LIAO, Théo MARKEZIC). The maintenance of the research infrastructure is ensured by the Lab Manager (Christelle GRUFFAZ) and supervised by the Principal Investigator (Alexandre SMIRNOV).

Table 7 . Data quality measures & criteria

 7

	Technical	Completeness (all samples are present, all parameters & settings are known
		& kept constant); functionality of the instrument & reagents (calibration,
		absence of obvious artefacts, maintenance); authentication &/or
		certification of internal & external research materials (cell lines, strains,
		plasmids, antibodies etc); compliance with a registered protocol;
		compliance of the protocol with established standards; sample integrity
		(absence of degradation, aggregation, or another undesirable
		modification); signal-to-noise ratio; dynamic range; saturation; number of
		events (e.g., in MS); CI of measurement; FDR; resolution; coverage;
		compliance of the behaviour of standards & controls with previously
		reported observations ("typical picture")
	Design	Presence of negative & positive controls; standards; complementation;
		optimal design of time or concentration series (within the dynamic range);
		complete combinatorial design; uniformity of measurement (e.g., all
		samples on the same gel/membrane or in the same run/session); statistical
		power & sample size estimation; correspondence between the
		experimental design & the statistical analysis approach (independence,
		pairedness, distribution, homoscedasticity, & other assumptions; continuous,
		count, or categorical data)
	Reproducibility	Technical & biological replication; single blinding (where possible); cross-
		experimenter replication (where possible); cross-batch replication;
		statistical convergence (absence of overdispersion)
	Documentation The experiment is completely described in the lab book, data follow the
		conventional vocabulary, are accompanied by properly registered &
		complete metadata & referenced in CER
	Digital	Data can be opened & modified with original software; data can be
		extracted & converted into a widely accepted format without losing
		information, quality, or interoperability; unambiguous association between
		data, metadata & the corresponding research resources (protocol, cell
		lines, strains, plasmids, oligonucleotides, antibodies, external datasets);
		fidelity of digitalised images; absence of non-documented or irreversible
		modifications to original files
	Re-used external data are normally expected to follow the same standards.
	However, data-specific checks need to be performed and eventual deviations from

the norm flagged in order to establish whether the external data in question require censoring. Inclusion guidelines for such data are provided in Table

8

. Filtering parameters and the decision to censor select data are systematically justified and included in the metadata. For all types of external data, permanent unique identifiers and duly documented provenance are required for inclusion. InsuRAF -Data Management Plan Version 3 -December 26, 2023

Table 8 . Inclusion guidelines for external data

 8

	Protein	The sequence is complete; experimental design, as reported in the original
	sequence,	publication, makes unlikely data contamination; independent sequencing of
	conservation,	other isolates of the same strain, other strains of the same species, or other
	phylogenetic	species of the same genus strongly support the sequencing variant; specifics
	distribution	of the genetic code are correctly captured (verified with ExpasyTranslate);
		NCBI BLAST confirms the identity of the entry & finds highly similar sequences in
		sister clades; COBALT confirms their clustering against selected outer groups;
		hallmarks of the protein family are clearly recognisable; the choice of the
		canonical splice isoform is based on well-described homologues from model
		species; significantly deviating sequences (COBALT) are inspected
		individually for misannotation
	Protein	Quality of the model is evaluated based on the experimental details in the
	structure	original publication & with the help of NGL Viewer (built in RCSB PDB) for the
		quality of fit & chain geometry
	Gene	The sequence is complete & is translated in silico into a protein that satisfies
	sequence	the above criteria
	Genome	The genome must be assembled to at least the chromosome level
	sequence
	MS data	Accompanied by proper metadata reporting on provenance, experimental
		protocol, & original publication
	Data from	High technical standard, as commonly required in the field; independent
	publications	corroboration (wherever applicable)

  section 1), as guaranteed by French law (article L342-3 du Code de la Propriété Intellectuelle) that implements the Directive 96/9/EC of the European Parliament and of the Council. Specifically, no third-party intellectual property or sui generis rights were or are expected to be affected. The data deposited in the wwPDB are open-access without copyright restrictions. However, the wwPDB Deposition Policies and wwPDB Biocuration Procedures (version 5.2; April 2023) reserve the authorship rights to Entry Authors, Contact Authors and Citation Authors. Furthermore, the re-use of deposited third-party data is subjected to specific rules, as defined by the corresponding repositories. The ProteomeXchange Consortium data re-use requirements are outlined in the Guidelines for handling ProteomeXchange reprocessed datasets (version 1.0.2; September 2019): the unique dataset identifier (PXD) should be cited, reprocessed data linked to the source PX dataset, reprocessed PX XML files should respect specific formatting. The SOLEIL data re-use requirements are outlined in the SOLEIL Data management policy (DSI-DU-P-0056; October 2, 2018): wherever appropriate, the Main Proposer or the Principal Investigator of the dataset should be contacted in order to inform them, propose collaboration or co-authorship; the source of the data, citing the unique persistent identifier and any publications linked to the same raw data, should be acknowledged.

	Section 5b more specifically deals with the open-access publication of datasets and
	documents associated with the InsuRAF project and cites the corresponding legal
	norms and community standards.

  The Group 2 data are formatted and deposited to appropriate trusted data repositories, according to Science Europe recommendations (Practical guide to the International alignment of research data management, January 2021) and established standards in the field. Key mass spectrometry data are deposited in the ProteomeXchange Consortium (via the PRIDE repository). Microscopy data are deposited to BioImage Archive (BIA) or Image Data Resource (IDR). Source codes are deposited on GitHub. The deposited data follow the corresponding policies and guidelines for formatting, storage, and sharing, as outlined in sections 4b, 5b, 5c, and 5d. The deposition to these selected databases is free of charge and, at the scale of the InsuRAF project, without effective size constrains. Foreseeable uses of the data include but are not limited to follow-up, replication or comparative studies, reanalysis, benchmarking, algorithm training, and database creation. Below are outlined some specific rules governing data deposition, archiving, and withdrawal in the repositories concerned by the present DMP.

  Recherche Data InsuRAF -Data Management Plan Version 3 -December 26, 2023Gouv does not store intermediate data and does not perform scientific quality checks; however, it does provide curation (including post-deposition, long-term curation) and formal validation of completed datasets submitted to the repository. Recherche Data Gouv policies enable deposition either in open or reserved access (the latter is possible for datasets that constitute a legal exception to the openaccess principle, e.g. professional or commercial secret, personal data). As in the other repositories mentioned above, data deposited to Recherche Data Gouv are findable and citable. Curators reserve the right to delete provisional submissions, modify submissions or withdraw published datasets or their versions from circulation, upon justification.

	Other trusted repositories will be considered in agreement with Science Europe
	guidelines and journal recommendations.
	Some Group 2 data (e.g., images, tabulated or graphed data) are directly published
	in the corresponding articles. The present DMP is deposited and updated, as
	described in section 6a, on Zenodo under Creative Commons Attribution 4.0
	International (CC BY) licence and communicated to ANR as a specific project
	deliverable.
	As a general rule, the default license for deposited InsuRAF data is, wherever
	possible, Creative Commons Attribution 4.0 International (CC BY).
	The versioning of deposited data generally follows RDA recommendations (Klump &
	al. Principles and best practices in data versioning for all datasets big and small,
	version 1.1; April 6, 2020). In particular, ProteomeXchange Consortium announces
	new versions of deposited PX datasets and enables the preservation and tracking of
	all versions of a dataset in ProteomeCentral (Data submission guidelines for the
	ProteomeXchange Consortium, version 3.0.1; October 13, 2019). Moreover,
	ProteomeXchange Consortium distinguishes the terms 'revision' (previously 'version')
	and 'reanalysis' of PX datasets. The former refers to technical updates on data or
	metadata without changing the original intent of the submission; new revisions
	render the previous ones obsolete. By contrast, 'reanalysis' is reprocessing of original
	raw data to achieve new results; it does not imply that other reanalyses are obsolete
	and does not supersede them. The ProteomeXchange Consortium has a specific
	policy regarding PIDs associated with reprocessed datasets (Guidelines for handling
	ProteomeXchange reprocessed datasets, version 1.0.2; September 2019).

Table 9 . Records management metadata file organisation (for archiving)

 9

	Entry	Description
	1. Title	"Records management metadata for the experiment NNE#####"
	2. Creator	Person (name, ORCID) who created the metadata file
	3. Subject	"Records management metadata"
	4. Description Concise & dated description of significant events accompanying the
		archiving procedure (e.g., revision of metadata; format conversion,
		movement or suppression of select data & the reasons for this) & the
		subsequent history of the archived dataset (e.g., copying, re-use in another
		experiment in house or by authorised external users, publication etc)
	5. Publisher	"Université de Strasbourg"
	6. Contributor Person(s) (names, ORCIDs) &/or institution(s) who perform archiving and
		manage the archive
	7. Date	Date of the last modification
	8. Type	"CER experiment dataset"
	9. Format	Name of the folder in which the archived data are classified ("NNE#####")
	10. Identifier	ID of the experiment ("NNE#####")
	11. Source	Primary or secondary (in the case of data re-use or re-analysis)
	12. Language	"English"
	13. Relation	IDs of other experiments &/or data or metadata to which the present
		dataset is related in terms of deliverables, continuation, replication,
		modification, re-use or re-analysis
	14. Coverage	Time period between the beginning of the dataset & the last modification
		of its records management metadata; physical location of the archive
	15. Rights	"IPR Unistra"

Table 10 . Records management metadata file organisation (for suppression)

 10

	Entry	Description
	1. Title	"Records management metadata for the experiment NNE#####"
	2. Creator	Person (name, ORCID) &/or institution who created the metadata file
	3. Subject	"Records management metadata"
	4. Description	Concise & dated description of the reasons & the circumstances of the
		dataset suppression & the subsequent history of the remaining metadata
		(e.g., copying, damage, or loss); person (name, ORCID) who authorised the
		suppression (usually, Principal Investigator, Alexandre SMIRNOV)
	5. Publisher	Université de Strasbourg
	6. Contributor Person(s) (names, ORCIDs) &/or institution(s) who performed the dataset
		suppression
	7. Date	Date of the last modification
	8. Type	CER experiment dataset
	9. Format	Name of the folder in which the archived data are classified ("NNE#####")
	10. Identifier	ID of the experiment ("NNE#####") & a complete list of all suppressed files
	11. Source	Primary or secondary (in the case of data re-use or re-analysis)
	12. Language	English
	13. Relation	IDs of other experiments &/or data or metadata to which the present
		dataset is related in terms of deliverables, continuation, replication,
		modification, re-use or re-analysis
	14. Coverage	Time period between the beginning of the dataset & the suppression;
		physical location of the archive
	15. Rights	IPR Unistra

The data and metadata are stored on the office computers and monthly backed up on two 1-Tb hard drives which are kept in a different location. Additionally, primary data are stored on original instruments and on the servers of the services and collaborators who generated them (e.g., SOLEIL), ensuring that several copies of the most important data are preserved in geographically distinct locations. The Seafile cloud storage of the University of Strasbourg is used to store and share between collaborators the research resources of the laboratory and some data. A more reliable, permanent, and spacious solution for heavy data storage is expected to be provided by the Data Centre of the University of Strasbourg.

All primary data are read-only to avoid unintentional modification.

The storage of intermediate data and metadata is regulated by the French law acts (Circulaire du 2 novembre 2001 relative à la gestion des archives dans les services et établissements publics de l'Etat).

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

The recoverability of the data is ensured by the multiplicity of stored copies resulting from monthly backups of all data. In the event of an incident, a complete copy of all the data will be reconstituted from backup on a reliable machine.

The access to the research infrastructure is open to all GMGM researchers involved in the InsuRAF project. The access of GMGM team members to the data is controlled by the Principal Investigator (Alexandre SMIRNOV) or directly by the Creators of the data. External collaborators receive relevant data and metadata upon request handled by the Principal Investigator (Alexandre SMIRNOV) via protected Seafile links. This policy is reciprocal. Non-collaborators in general do not have access to the data during the research, unless those are already deposited in open repositories and/or published (see section 5). Exceptions are handled individually by the Principal Investigator (Alexandre SMIRNOV) upon consultation with collaborators. Lab books are stored in a securely locked team's office; only in exceptional cases, the Principal Investigator (Alexandre SMIRNOV) may authorise their removal from the laboratory by Creators or other authorised participants of the InsuRAF project.

No sensitive data were treated or are expected to be treated in the frame of this project.

General guidelines for data handling, protection, and sharing are governed by a specific policy of the University of Strasbourg, as a member of the SupDPO network (La Vie d'une Donnée au regard des réglementations "CRPA", "RGPD" et "Patrimoine", v1.0, June 2019), and by the CNRS Policy of Security of Information Systems (PSSI). Data collected at the synchrotron SOLEIL are subject to the SOLEIL Data management policy (DSI-DU-P-0056, October 2, 2018), which regulates the access to, re-use, and publication of the data (see sections 4 and 5 Ownership of the primary data obtained at the synchrotron SOLEIL is regulated by the SOLEIL Data management policy (DSI-DU-P-0056; October 2, 2018) and should be interpreted in the sense that all derived products (results, data interpretation, IPR), being performed by participants of the InsuRAF project, remain the property of the University of Strasbourg (Code de la propriété intellectuelle; October 3, 1996; section R611-12).

The data deposited in the ProteomeXchange Consortium remain the property of the Principal Investigator and of the PRIDE Submitter even after their public release, as specified in the Data submission guidelines for the ProteomeXchange Consortium (version 3.0.1; October 13, 2019).

IDR encourages authors to submit imaging datasets under the CC BY license (with licensing information included in the accompanying metadata) to facilitate their widest re-use (Submission Guidelines v1.0; March 2017). Authors retain copyright, while IDR receives a license to publish the data on behalf of the authors.

BioImage Archive policies (version 1.1) make deposited data available under the CC0 license by default. This is potentially problematic since, unlike CC BY, CC0 does not protect author rights and leaves citation of the data at re-users' discretion. However, the same policies acknowledge that some deposited datasets are available under different licenses (indicated as dataset attributes). InsuRAF will strive to deposit microscopy data under the CC BY license. BIA has a removal procedure if the ownership or provenance of datasets is called into question (BioImage Archive Policies, version 1.1; see also section 5a). InsuRAF -Data Management Plan Version 3 -December 26, 2023

provided that the suppression does not affect the completeness of the archived dataset. In either case, suppression is systematically motivated and authorised in the accompanying records management metadata.

Long-term curation of the archive is ensured by the Lab Manager (Christelle GRUFFAZ) and by the Principal Investigator (Alexandre SMIRNOV). The archived datasets are not subject to suppression; their preservation is assured by the University of Strasbourg. In the case where the activity of the latter is ceased, the archived datasets should move to an appropriate state archive, according to the French law regulations (Code du patrimoine, article L212-5).

The legal requirements for the re-use of published data, data archiving, and destruction are fixed by the French law and can be found in the Guide pratique de la publication en ligne et de la réutilisation des données publiques ("Open data") Specific data types and the software required to access and re-use the data deposited in the ProteomeXchange Consortium are described in the Data submission guidelines for the ProteomeXchange Consortium (version 3.0.1; October 13, 2019) and in PRIDE recommendations.

According to the SOLEIL Data management policy, access to raw data, metadata and results stored by SOLEIL is possible for registered users via a searchable on-line catalog. SOLEIL engages to make available means to read, reduce and/or process raw data. Download of the data may be subject to volume restrictions.

BIA, while accepting a number of proprietary formats, encourages submission in widely supported formats, e.g. OME-TIFF or OME-NGFF. All users can access and download deposited data.

Image Tools Resource (ITR) of IDR provides and maintains links to a wide variety of software tools to work with data.

Recherche Data Gouv (Displaying and exploring data, April 3, 2023) offers multiple options to explore and download deposited data in function of their format and access conditions. Any user can explore and download published datasets; only authorised users can access unpublished datasets.

Zenodo General Policies (version 1.0) guarantee access to deposited data (in their original format) to unregistered users. InsuRAF -Data Management Plan Version 3 -December 26, 2023

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

All selected trusted repositories assign persistent identifiers (PIDs) to deposited datasets with modalities following A Persistent Identifier (PID) policy for the European Open Science Cloud (October 2020). The ProteomeXchange Consortium associates all deposited datasets with its own unique and persistent identifiers (PXD and RPXD assigned by ProteomeCentral). Similarly, BIA assigns its own accession codes to each directly submitted dataset; by contrast, BIA keeps the PIDs of datasets imported from partner repositories. IDR Submission Guidelines (version 1.0, March 2017) introduced idr-codes as informal accession numbers unique to each dataset; however, they encourage using DOI (automatically minted for each dataset) as a formal way of dataset citation. SOLEIL is set to assign unique persistent identifiers to both its experiments and datasets. Recherche Data Gouv and Zenodo assign DOI to all deposited documents. See also section 5a for the special case of data versioning. ORCIDs to identify authors and contributors are added to metadata wherever possible or required by repositories.

Data management responsibilities & resources

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

Data stewardship responsibilities and their assignments are outlined in Table 11.

The Principal Investigator (Alexandre SMIRNOV) is responsible for the DMP implementation, review, and revision.

This 3 rd version of the DMP is the definitive one; it is not subject to updating anymore. The time effort from each data steward is estimated at ~1 person•month/year. It makes part of contract or statutory obligations of the stewards. Financial costs include expenses for hard drives (~600 €) and eventual access to the Data Centre (in process of negotiation). Data storage in all selected trusted repositories is free of charge.


Damien Querlioz

Daniel Brunner

Elisa Vianello

Elisa Vianello L'

L'électronique pour le calcul -Projet ciblé BEP: BioElectronPhoton

and research institutions in France or abroad, or from public or private research centers.

  Photonique 3D : rapide, parallèle, basse consommation


Gaëtan Boissonneau

Andréa Tommasi

Fabrice Barou

Marco A 17 Lopez-Sanchez

Maurine Montagnat

Dynamic recrystallization and mechanical behavior of 14 Mg alloy AZ31: Constraints from tensile tests with 15 in-situ EBSD analysis 16

Keywords: Dynamic recrystallization, softening, texture, hexagonal 20

We conducted tensile tests on AZ31 samples with in-situ SEM-EBSD acquisition at 250°C and 10 -3 s -1 to study the evolution of dynamic recrystallization and its effect on the mechanical behavior. To investigate the entire deformation range up to failure at 65-67% engineering strain, stepwise experiments were conducted with in-situ EBSD acquisition at 2-5% strain intervals and repolishing of the samples at 15% strain intervals. All experiments show a consistent mechanical behavior characterized by a transition from hardening to quasi-steady state at ∼10% strain, followed by softening for strains greater than 35%. The bulk intragranular misorientation, quantified by the mean kernel average misorientation, increases steadily. Analysis of the EBSD maps shows that the quasi-steady state is associated with dominant dislocation reorganization (polygonization), whereas the onset of softening is linked to a net and continuous increase in the recrystallized fraction. In situ EBSD mapping documents the local discontinuous nature of continuous dynamic recrystallization: (1) nucleation of strain-free grains by bulging and subgrain rotation, (2) grain growth, (3) re-accumulation of dislocations substructures and formation of new nuclei. Analysis of the textures shows that dynamic recrystallization slows down rotation and strengthtening of the textures. The observed steady state and softening behaviors result therefore from both geometrical (texture-induced) and microstructural (dislocation-related) softening due to dynamic recrystallization.

samples. The acquisition conditions, area and step sizes for all maps are 109 summarized in Supplementary Material Table T1. The open-source MTEX MATLAB toolbox v5.6.1 (https://github.com/mtex-112 toolbox/mtex) has been employed to treat and analyze the EBSD data. Mea-113 surements with a mean angular deviation higher than 1.3°were neglected.

114

Grain boundaries were identified using a 7.5°misorientation threshold and 115 smoothed (two iterations). Grains defined by less than four pixels were 116 dropped out from the dataset. EBSD data was smoothed using a half-117 quadratic filter within each grain. The grain size threshold includes nuclei formed by any processes but keeps no 152 memory of fast-growing RX grains; it allows to probe the grain growth rate.

153

The absolute values of the two thresholds are chosen empirically. We present All experiments display a consistent mechanical behavior well illustrated by 162 the true stress/engineering strain curves for the two samples deformed up to 163 the highest strain (Fig. 1). Sample H (purple curve in Fig. 1) was deformed 164 outside the SEM without interruption until failure to be used as a reference.

165

The true stress/engineering strain curve displays an elastic loading phase of 166 up to 2% strain, followed by a hardening stage up to 10% strain. From 10% 167 to ∼30% strain, it exhibits a quasi-steady state behavior, which is followed 168 by softening up to ductile failure at 63% strain. Optical inspection of the 169 evolution of the sample shape with increasing strain did not document any 170 progressive necking, but a catastrophic development of a semi-brittle shear 171 band at the end of the experiment (see Supplementary Material Fig. S3). T1).

216

The grain size shows a two-step evolution (Fig. 2

Recrystallization processes 252

The evolution of the microstructure from the annealed state up to 12% strain 253 is illustrated using KAM maps of sample X (Fig. 4). Before deformation, 254 grains have smooth boundaries and sizes ranging between 30 to 100 µm. A marked switch in mechanical behavior, from quasi steady-state to soften-296 ing (Fig. 1), accompanied by stabilization of the previously decreasing grain 297 size (Fig. 2.b) and a sudden increase in the recrystallized fraction (Fig. 3) 298 is observed around 35% engineering strain. The evolution of the microstruc-299 ture after this transition is well illustrated by data for sample X between 300 35% and 47% engineering strain (Fig. 6). In situ EBSD data for the 47% to 301 65% strain interval provide similar observations. The grain size distribution 302 is strongly bimodal with coarse grains (equivalent diameters ≥100 µm) and This DRX grain grew fast at the expenses of its highly deformed neighbors, 323 from 35% to 41% strain, while maintaining its intragranular structure almost 324 free of dislocation substructures. At 44% growth slowed and dislocations 325 started to accumulate, as documented by the build-up of substructures with 326 misorientations that continued to increase up to 47% strain. This sequence 327 also documents the formation of new DRX grains along the boundaries of 328 this grain after 44% strain. The initial texture is characterized by a girdle of < c > axes oblique to the 331 tensile axis. We quantified the texture evolution by: (1) the change in the 332 angle between the normal to the < c >-axis girdle and the tensile axis and

333

(2) the intensity of the texture using a texture index proxy, the J-index (the 334 integral of the squared orientation distribution function [8]). With increasing 335 strain, the angle between the normal to the < c >-axis girdle and tensile axis, Then, the in-situ EBSD map sizes had to be kept small to prevent significant 382 annealing and are therefore too small to be representative volume elements.

383

To mitigate that, larger dimension maps were acquired post-mortem for most T1) further en-387 sures the statistical representability of the bulk microstructural parameters.

388

For the mechanical response, the data from Sample H, deformed outside the 389 SEM without interruption until failure, is used as a reference. The DRX fraction remains limited up to 35% strain. Onset of widespread nu-414 cleation is associated with (1) a marked change in mechanical behavior, from 415 quasi steady-state to softening (Fig. 1), (2) stabilization of the previously 416 fraction (Fig. 3). We infer that this rather long incubation period is needed 418 to construct the dislocation substructure. Analysis of the KAM maps shows 419 that substructure formation is more active during the hardening and steady-420 state phases of the experiments (Figs. 4 and5) than during the softening 421 phase (Fig. 6). The long incubation period suggests that, at the present 422 experimental conditions, recovery may have delayed the onset of recrystal-423 lization. However, even when nucleation is dominated by bulging, the bulges 424 are closed by subgrain boundaries that evolve into grain boundaries (Fig. 425 6.b), indicating that polygonization plays an important role in nucleation [START_REF] Chauve | Main-593 price, Investigation of nucleation processes during dynamic recrystal-594 lization of ice using cryo-EBSD[END_REF]. The difference between the recrystallized fractions defined using the GOS or 440 the grain size stems from the fact that the two thresholds focus on different 441 aspects of the recrystallization process (Fig. 3). The GOS criterion only 442 considers the intragranular dislocation density. Grains are identified as RX 443 grains until they re-accumulate dislocations by deformation. The grain size 444 criterium is more sensitive to grain growth. It also identifies as RX grains 445 those formed by subgrain rotation, which may have dislocation structures 446 inherited from the parent grains and hence GOS values >1°. This might 447 explain the slightly higher RX fractions determined using the grain size cri-448 terium below 35% strain. However, the steady increase in the RX fraction 449 after 35% strain determined using the grain size criterium while the RX frac- 4: Microstructure evolution in the early stages of the experiments, illustrated by first order KAM maps obtained in situ at 0%, 6%, 9%, and 12% engineering strain for sample X. Grain boundaries, calculated using a 7.5°misorientation threshold, are represented as black lines. (a) Full size maps, in which the recrystallized grains identified using a 1°GOS threshold are coloured in blue. (b) Zoom on the area defined by the red square in (a); in these detail maps, KAM data for all grains are displayed, so that its evolution with strain may be followed.

Figure 5: Microstructure evolution in the 23% to 38% strain interval, illustrated by in-situ first order KAM (left column) and mis2mean maps (right column) of sample D at 23%, 28%, 33%, and 38% engineering strain. Grain boundaries calculated using a 7.5°misorientation threshold are represented as black lines. (a) Full size maps, with recrystallized grains identified using a 1°GOS threshold coloured in blue. (b) Zoom on the area defined by the blue and the red rectangles in 23% and 38% engineering strain maps. A grain interpreted as formed by nucleation by subgrain rotation between 33% and 38% strain, is highlighted with a green boundary in the 38% strain detail maps, note its strong intragranular misorientation.

Figure 6: Microstructure evolution in the softening stage of the experiments, illustrated by KAM maps obtained in situ for sample X at 35%, 38%, 41%, 44%, and 47% engineering strain. All maps but that at 47% strain, were acquired with a 1 µm step size; the map at 47% strain was acquired with a step size of 0.5 µm. To keep absolute KAM values comparable over the entire strain range, the KAM order has been adjusted: first order KAM data is presented for all maps except for that at 47% strain strain, which displays second order KAM data. Grain boundaries calculated using a 7,5°misorientation threshold are represented by black lines. (a) Full size maps, in which recrystallized grains identified using a 1°GOS threshold are coloured in blue. (b) Zoom on the area defined by the blue rectangle in (a); dark green and purple circles are used to highlight areas showing nucleation events. (c) Zoom on the area defined by the red rectangle in (a), which displays the growth and re-accumulation of local misorientation in a recrystallized grain (highlighted in light blue) that is tracked using its location and crystallographic orientation from map to map. Figure 7: Evolution of the texture with engineering strain: (a) orientation of the texture, defined by the angle between the normal to the <c> axis girdle and the traction direction and (b) texture strength, defined by the J-index. Symbols in white, gray, and black correspond to full orientation data in the map, considered as one orientation per pixel. Coarser black symbols mark data from larger, post-mortem maps. To estimate the spatial variability of the data and the representativity of the smaller in-situ maps, these large maps (area > 1.25 mm 2 ) have been re-sampled as multiple smaller maps with areas similar to that of the in-situ ones (∼0.2 mm 2 ) to obtain the mean and the standard deviation, represented by the errorbars, of the distributions. For comparison, the texture of the recrystallized fraction identified using a 20 µm threshold in each map is represented by blue symbols; as for the full orientation data, the symbol sizes are proportional to the area of the map. The full lines indicate the texture evolution predicted by a 2 nd order viscoplastic self-consistent simulation for uniaxial traction with normalized critical resolved shear stresses (CRSS) for the basal<a>, prismatic<a>, and pyramidal<a+c> systems of 1, 40, and 40 MPa and as the initial texture that of the starting material.

118 119

 118 We imaged and quantified the evolution of the microstructure based on:[START_REF] Sakai | Dynamic 579 and post-dynamic recrystallization under hot, cold and severe plastic 580 deformation conditions[END_REF] 120 the intragranular misorientation, (2) the grain sizes, and (3) the recrystallized 121 fraction. The intragranular misorientation produced by the accumulation of 122 geometrically necessary dislocations (GND), was estimated based on: (1) 123 the kernel average misorientation (KAM), which is the average value of the 124 misorientation between a pixel and its neighbors, (2) the grain orientation 125 spread (GOS), which is the mean deviation of the local orientations relative 126 use a joint threshold. However, analyzing the RX fraction defined based each 147 of these criterium separately allows to highlight different aspects of the RX 148 process. The GOS threshold allows to discriminate newly formed RX grains 149 with low dislocation densities from those that have a dislocation substructure 150 due to either nucleation by polygonization or deformation subsequent to RX.151

154

  results for a GOS threshold of 1°and an equivalent grain diameter of 20 µm, 155 based on the analysis of the KAM maps and grain size distributions. Dif-156 ferent grain size and GOS threshold values result in different recrystallized 157 fractions but define similar evolution trends (see Supplementary Material

Fig

  Fig.S2).

172 173 1 .Fig. 1 3 . 2 .

 1721132 Fig. 1 present data for EBSD acquisition at 150°C, whereas those displayed as 187

241 242

 241 Defining recrystallized grains based on a 20 µm equivalent diameter threshold 243 (Fig.3.b) results in low RX fractions (<5%) up to 10% strain. Data for 244 strains between 10% and 35% strain show a higher dispersion, but the RX 245 fraction remains below 10%. Similarly to the RX fraction defined based on 246 the GOS criterium, a sudden increase in the RX fraction is observed at 35% 247 strain. Both samples deformed to higher strains display a steady increase 248 in recrystallized fraction up to the end of the experiments, but the rates of 249 increase differ between the two experiments. The maximum RX fraction, 250 observed for sample F at 47% engineering strain, is of 28%.

  251

255

  Due to the pre-deformation annealing, KAM values are mostly below 1°, 256 thus most grains are identified as recrystallized based on the GOS criterium. 257 A few grains preserved scarce subgrain boundaries. At 6% engineering strain, 258 most grains display significant intragranular misorientations and the RX frac-259 tion based on the GOS is reduced to 15% (Fig. 3.a). Accumulation of dis-260 locations and formation of subgrain boundaries is spatially heterogeneous, 261 varying from grain to grain, but, in most cases, densities are stronger in the 262 vicinity of grain boundaries (on average within <10 µm of the boundary).263 Apparent (2D) grain sizes hardly evolved, but grain boundaries became more 264 serrated and local misorientations are intensified, leading to a decrease of the 265 RX fraction defined based on the GOS to 3-4% at 12% engineering strain. 266 At strains >10%, small grains (<10 µm) are observed locally, but these small 267 grains do not always have GOS <1°. In summary, up to ∼10% engineering 268 strain, the evolution of the substructure due to progressive accumulation of 269 grain boundary geometry. This observation indicates that, under the present 271 experimental conditions, dislocation mobility has faster kinetics than grain 272 boundary mobility. 273 274 Analysis of the microstructure between 23% and 38% engineering strain for 275 Sample D documents continuation of the same trend (Fig. 5.a). The more 276 strained is the sample, the more serrated are the grain boundaries. The 277 progressive increase in the misorientation across subgrain boundaries is well 278 illustrated in the Mis2mean maps (right panel of Fig. 5.a). A zoom in the 279 abnormally coarse grain that occupies most of the lower part of the map 280 (Fig. 5.b) shows that the strong orientation gradient across the central part 281 of the grain is accommodated by a network of low-angle boundaries, 10-20 282 µm wide. This network became more complex and misoriented with strain 283 but did not evolve into a well-defined grain boundary. Most grains still have 284 sizes in the 30 to 100 µm range, but small DRX grains are observed in all 285 maps. The RX fraction based on GOS remains almost constant (Fig. 3.a), 286 but that based on grain size slowly increases (Fig. 3b). The discrepancy 287 between the two measures may be partially explained by the contribution of 288 polygonization and subgrain rotation to DRX. This process is well illustrated 289 by the DRX grain highlighted in green in Fig. 5.b, in which the new grain 290 boundaries, formed by polygonization, enclose preexisting substructure. This 291 process contrasts with nucleation by bulging, in which grain boundary mi-292 gration cleans the dislocation substructure, producing DRX grains with little 293 internal misorientation.294 295

  303clusters of small DRX grains (equivalent diameters of 3-20 µm). Most DRX 304 grains show little intracrystalline misorientation (GOS <1°). In the 35% to 305 65% strain interval, the DRX clusters show fast microstructural evolutions 306 relative to the coarse grains. The RX fraction defined based on the grain 307 grains, whereas that based on the GOS remains stable.

309 310

 309 Relative to lower strains, which were dominated by polygonization, the con-311 tribution of nucleation and grain boundary migration to the evolution of the 312 microstructure increases. Evidence of nucleation by bulging (grain boundary 313 migration) with closure of the bulge by a subgrain boundary is widespread. 314 This process is illustrated in Fig. 6.b, in which two grains formed by DRX 315 are highlighted. The kinetics of the nucleation in the two cases is apparently 316 distinct: the grain highlighted in purple formed progressively, whereas the 317 one highlighted in green formed suddenly between 41% and 44% strain onto 318 a previously slowly migrating boundary. The in-situ EBSD observations for 319 this strain range highlight the discontinuous nature of the processes at the 320 grain scale. The zoom in Fig. 6.c documents the evolution of a DRX grain, 321 which was tracked based on its position and crystallographic orientation.

  322

329 3 . 4 .

 34 Texture evolution 330

336

  initially at 30-35°, decreases (Fig.7.a). However, the texture reorientation 337 rate progressively slows down and a quasi-steady orientation of the normal 338 to the < c >-axis girdle at ∼20°to the tensile axis is attained after 35% 339 engineering strain. The evolution of the orientation of the DRX grains (seg-340 mented based on the grain size) is, however, different. They initially display 341 similar, but more dispersed, orientations than those of the parent grains, 342 which control the bulk texture. However, after 35% strain, DRX grains have 343 axis girdle and the tensile axis (ca. 24°at strains >45%).

345 346

 345 The texture intensity does not vary significantly with increasing strain, with 347 an almost constant bulk texture index around 4 for the datasets obtained on 348 large areas at the start or after the experiments (Fig. 7.b). Higher texture 349 indexes are estimated based on the smaller maps collected in-situ during the 350 experiments, but these data are biased by the presence of a few coarse grains 351 that occupy large area fractions of these maps (cf. Figs. 4 to 6). The DRX 352 grains texture shows, like many other quantities in the present experiments, 353 a change around 35% engineering strain. Up to 35% strain, it is slightly 354 more dispersed than the bulk texture. Its dispersion then increases up to 355 40% strain and then it stabilizes at texture indexes between 2 and 2.5. 356 357 To quantify the effect of DRX on the texture evolution, we compare the 358 measured textures to that predicted for uniaxial tension using a polycrystal 359 plasticity model, in which deformation is solely accommodated by dislocation 360 glide: the viscoplastic self-consistent model (VPSC [9, 10]). The simulation 361 was performed using the VPSC7 code [11] with a 2 nd order linearization 362 procedure, normalized critical resolved shear stresses (CRSS) for the basal 363 < a >, prismatic < a >, and pyramidal < a + c > systems of 1, 40, and 40 364 MPa with the EBSD maps from the annealed state of sample Y as a reference 365 texture. The ratios between the CRSS of the different slip modes are derived 366 from Zhang et al. (2021) [12]. Since the microstructural observations point 367 to effective recovery, hardening is not implemented in these simulations. The 368 initial texture is that measured for the starting material. VPSC models 369 predict continuous concentration and reorientation of the texture, though 370 at a progressively decreasing rate, towards parallelism between the normal 371 to the < c >-axis girdle and tensile axis (continuous lines in Fig. 7). The 372 texture evolution documented in the present experiments clearly deviates 373 from the predictions of these DRX-free models. DRX produces therefore 374 both dispersion and reorientation of the texture.

376 4 . 1 .

 41 Experimental limitations 377 The first limitation of the present study stems from the interruption of the 378 deformation for in-situ acquisition of the EBSD data. Reducing the temper-379 250°C during the mapping may result in partial annealing and thus recovery.

  381

384samples.

  These wide-ranging maps are used as reference to estimate the rep-385 resentability of the in-situ maps. The large number of EBSD maps acquired 386 in the present study (61, cf. Supplementary Material Table

390 391

 390 Due to the deterioration of the surface, acquisition of data on a single surface 392 is limited to 15% cumulated strain before the samples had to be re-polished.393However, the data presented in section 3.3 show that such a strain interval is 394 sufficient to document the local DRX evolution. The analysis of multiple tests 395 with overlapping strain intervals allows to verify the reproducibility of these 396 observations and the sample scale evolution. Yet, the onset of widespread 397 nucleation/growth around 35% was not observed within a single experiment, 398 but by comparing different experiments. Finally, EBSD providing a two-399 dimensional description of the microstructure at the sample surface, growth 400 of grain nucleus out of the observation plane cannot be discriminated from 401 nucleation on the plane.

402 4 .

 4 2. DRX processes 403 The present experiments document continuous DRX in AZ31. This process 404 involves: (1) accumulation and reorganization of dislocations in low-angle 405 boundaries networks, i.e., polygonization (Figs. 4 and 5) and (2) grain for-406 mation processes (Fig. 6), with nucleation by an association of bulging and 407 subgrain rotation (Fig. 6.b) and growth of the RX grains by grain boundary 408 migration (Fig. 6.c). In most cases, new RX grains initially show low dislo-409 cation densities, documenting the cleaning of the dislocation substructure by 410 migrating boundaries (Fig. 6.c). However, as they grow, they re-accumulate 411 dislocations and re-recrystallize (Fig. 6.c).

426 427

 426 Comparison between the experimental textures and the texture evolution 428 predicted by VPSC simulations highlights that during DRX both polygo-429 nization and nucleation/growth processes slow down the reorientation of the 430 texture towards parallelism between the main Burgers vector, here [1210], 431 and the tensile direction (Fig.7). The experimental textures show a con-432 stant orientation for all strains >35%, characterized by a bulk orientation of 433 the normal to the < c >-axes girdle at ∼20°to the tensile axis. RX grains 434 are systematically more oblique to the tensile axis, having on average the 435 normal to the < c >-axes girdle at ∼24°to the tensile axis for all strains 436 >45%. These observations suggest a stronger effect of nucleation/growth on 437 the texture evolution.

450

  tion defined based on the GOS remains stationary results from slow grain 451 growth relative to nucleation and build-up of dislocation substructures in the 452 present experiments. This is corroborated by the marked grain size reduction 453 (Fig. 2.b). 454 13 ing discontinuous network of small-grain clusters (Fig. 6.a). This suggests 457 that nucleation is mainly controlled by plastic strain incompatibilities, re-458 laxing local stress concentrations. The higher density of grain boundaries 459 within the clusters may also favor further recrystallization within them, as 460 it will favor the formation of dislocation pile-ups [13]. The RX fraction de-due to dislocation pile-ups [13]. We hypothesize that fast re-recrystallization 493 of DRX grains may avoid hardening by Hall-Petch processes during DRX.

  softening by slowing down the texture evolution and 496 therefore avoiding (or reducing) the geometrical hardening relative to that 497 expected in absence of recrystallization. The relative contributions of the 498 microstructural and the textural effects of DRX to the observed softening 499 may be estimated by comparison between: (1) the mechanical behavior ob-500 served in the experiments, (2) the mechanical behavior predicted using the 501 VPSC approach described in section 3.4, and (3) instantaneous tensional 502 stresses predicted using the same VPSC model for the textures measured 503 at different strains (Fig. 8). This comparison highlights that the geomet-504 rical weakening due to a slower texture evolution in the experiments alone 505 could explain the quasi steady-state bulk mechanical behavior between 10 506 and 35% engineering strain, but cannot account for the bulk softening ob-507 served for strains >35%. The comparison also shows that the slower texture 508 evolution in the experiments starts before evidence for widespread nucleation 509 is observed. This suggests that polygonization may effectively slow down the 510 texture evolution and produce thereby significantly bulk softening. VPSC 511 predictions are dependent to the first order on the CRSS used for the differ-512 ent slip systems [9]. A less anisotropic single crystal behavior (lower contrast 513 between the CRSS of the basal and prismatic and pyramidal systems) will 514 result in slower texture evolution and weaker geometrical hardening without 515 DRX, but qualitatively the results will be similar. 516 517 Although nucleation is localized, affecting relatively small volumes (RX area 518 fractions <30%, Fig. 3.b) in the shape of spatially discontinuous clusters 519 (Fig.6.a), it produces bulk softening of the sample by relaxation of local 520 stress concentrations. Homogenization of the stresses within the sample by 521 DRX could explain tensile deformation to high strains without necking. In 522 contrast, the final deformation stages of sample H seem to indicate that 523 development of a throughgoing recrystallization domain at the sample scale 524 may result in strain localization, dramatic softening, and shear failure. The 525 present data raise an additional question: What phenomenon does control 526 the transition in macroscopic behavior between steady-state and softening: a 527 critical RX fraction or a percolation threshold characterizing the continuity 528 on a given scale (sample width) of the RX clusters? 529 controlled by the nucleation processes and the relative kinetics of nucleation, 568 grain growth and re-accumulation of dislocation substructures.

  569

Figure 1 :

 1 Figure 1: True stress/ engineering strain curves for all tests. Data for samples X and H, which cover the full strain range and are discussed in detail in the text, are highlighted in blue and purple, respectively. The lower panel details the experiments conducted on each sample: each line represents a continuous experiment with in-situ EBSD maps acquired without repolishing of the sample. Sample H was deformed without in-situ EBSD acquisition and is used as a reference.

Figure 2 :

 2 Figure 2: Evolution of the (a) intragranular misorientation and (b) grain size distributions with strain. Intragranular misorientation is defined by the 1st order Kernel Average Misorientation (KAM) and grain sizes, by the equivalent diameter. Data from multiple EBSD maps on a single or multiple samples at similar engineering strains were concatened to increase the statistics. The boxes define the first and third quartiles, the median is highlighted in red, and the extrem bounds of the whiskers represent the 10th and 90th percentiles of the data. The box color is function of the number of data points in each distribution, with darker colors marking the data with best statistics (graphic legends on the top of each plot).

Figure 3 :

 3 Figure 3: Evolution with strain of the recrystallized area fraction defined based on (a) a 1°GOS threshold and (b) a 20 µm equivalent diameter threshold. Symbol sizes indicate the total area of the EBSD map. To estimate the spatial variability of the data and the representativity of the smaller in-situ maps, the large maps (area > 1.25 mm 2 ) have been re-sampled as multiple smaller maps with areas similar to that of the in-situ ones (∼0,2 mm 2 ); this allows to estimate the mean and standard deviation, represented by the errorbars, of the recrystallized area fraction distribution in these maps.

Figure

  Figure4: Microstructure evolution in the early stages of the experiments, illustrated by first order KAM maps obtained in situ at 0%, 6%, 9%, and 12% engineering strain for sample X. Grain boundaries, calculated using a 7.5°misorientation threshold, are represented as black lines. (a) Full size maps, in which the recrystallized grains identified using a 1°GOS threshold are coloured in blue. (b) Zoom on the area defined by the red square in (a); in these detail maps, KAM data for all grains are displayed, so that its evolution with strain may be followed.

Figure 8 :

 8 Figure 8: Comparison between the (a) mechanical behavior of Sample H, which was deformed without interruptions and (b) that predicted by a 2 nd order viscoplastic selfconsistent simulation for a monotonic uniaxial traction experiment with normalized critical resolved shear stresses (CRSS) for the basal<a>, prismatic<a>, and pyramidal<a+c> systems of 1, 40, and 40 MPa and the initial texture of sample Y and the instantaneous tensional stresses predicted using the same VPSC model for textures measured at different engineering strains.

decrease with strain up to 35% engineering 219 strain and remain almost constant afterwards. Median equivalent diameters 220 evolve abruptly from >20 µm to ∼7 µm at strains >35%. Note, however, 221 that this shift in behavior has not been observed within a continuous ex- 222 periment, but between successive experiments. Moreover, due to the limited

	233	as the annealed grains start to accumulate dislocations. Despite some vari-
	234	ability among samples, due to the small mapped areas, the recrystallized
	235	fraction remains stable, below 5% up to 35% engineering strain. A sudden
	236	increase in the RX fraction is observed at ∼35% strain. In the 35% to 48%
	237	interval the RX fraction ranges between 7 and 12%. Thereafter, it fluctuates
	238	between 5 and 8%, but the last strain interval is documented by a single
	239	experiment. Post-mortem analysis of sample H documents higher RX frac-
	240	tions of 17% -20% with the highest fractions measured in the vicinity of the
		localized shear band.
	217	.b). All parameters de-
	218	scribing the grain size distribution (median, first and third quartiles, and
	maximum excluding outliers) 223
	224	area of the domains analyzed during in-situ mapping, boundary grains could
	225	not be eliminated from the dataset, biasing the estimation of the equivalent
	226	diameters towards lower values.
	227
	228	The RX fraction, that is, the area fraction of the map occupied by recrys-
	229	tallized grains, defined using a 1°GOS threshold (see section 2.3) is initially
	230	very high because of artifacts (Fig. 3.a). Indeed, undeformed samples have
	231	"statically" recrystallized fractions ranging between 88-91%. As deforma-
	232	tion proceeds, the recrystallized fraction drops quickly to low values (<5%)
		7

Acknowledgements

This work was supported by the European Research Council (ERC) un-571 der the European Union Horizon 2020 Research and Innovation programme 572 [grant agreement No 882450 -ERC RhEoVOLUTION]. We are grateful to 573 Christophe Nevado from Géosciences Montpellier, for his support in the 574 preparation of the EBSD samples. We thank Thomas Chauve for fruitful