# A W7 structured metadata framework for reinforcing data provenances in 2D/3D digitization workflows

Anthony Pamart, Quentin Vogel, Eloi Gattet, Daouda Ngom, Laurent Bergerot

► To cite this version:

Anthony Pamart, Quentin Vogel, Eloi Gattet, Daouda Ngom, Laurent Bergerot. A W7 structured metadata framework for reinforcing data provenances in 2D/3D digitization workflows. 11th International ISPRS / CIPA Workshop "3D Virtual Reconstruction and Visualization of Complex Architectures", Fabio Remondino; Roberto Pierdicca; Ramona Quattrini; Francesco Fassi, Feb 2026, Ancone, Italy. pp.351-358, 10.5194/isprs-archives-XLVIII-2-W12-2026-351-2026. halshs-05512234

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# A W7 structured metadata framework for reinforcing data provenances in 2D/3D digitization workflows

Anthony Pamart¹, Quentin Vogel¹, Eloi Gattet¹, Daouda Ngom¹, Laurent Bergerot¹

¹ Modèles et simulations pour l'Architecture et le Patrimoine, UPR 2002 MAP CNRS, Marseille, France.

**Keywords:** Metadata, Paradata, Data Provenance, real-based modeling, workflows, image-based modeling, range-based modeling, photogrammetry, lasergrammetry, computational photography

## Abstract

The documentation and provenance tracking of digitization workflows in Cultural Heritage (CH) face persistent challenges due to fragmented metadata practices and the absence of intuitive frameworks. This paper presents a W7-structured metadata framework, implemented through ANAMNESIS, an open-source platform designed to reinforce data provenance in 2D/3D digitization workflows. By systematically capturing the what, who, where, when, why, how, and which dimensions of digitization activities, the W7 model provides a structured, semantic approach to documenting critical technical and contextual details often lost in current practices. The platform operationalizes this framework with customizable schemas tailored to 2D/3D imaging workflows, ensuring traceability, reproducibility, and interoperability. Through real-case applications, the proposed approach not only preserves data provenance but also enables FAIR-by-design practices, empowering CH practitioners to contribute to a standardized, collaborative knowledge base.

## 1. Introduction

### 1.1 General Introduction

Digitization workflows have evolved alongside the technological advances since the early stages of Cultural Heritage (CH) applications. While the main stages—from capture to processing and analysis—remain unchanged, their underlying processes have grown increasingly complex. The methods used to create 2D/3D digital documentation also vary widely, shaped by practitioners' habits, tools, and experiences. This variability, coupled with the constant adaptation of protocols to CH artifacts, often results in a gap in reproducibility. Despite the historical and persistent weaknesses in data provenance and information traceability, experts' choices throughout the modeling process directly influence the quality of the digital output. If we consider real-based modeling as a form of sampling from the physical world, other scientific domains would never reuse a sample without comprehensive knowledge of its content (Plumejeaud-Perreau and et Al., 2019). Yet, this fundamental principle is frequently overlooked in digital sampling—even though the stakes remain equally high. Today, 2D and 3D data are increasingly shared, exchanged, and reused, driven by the rise of open science and FAIR principles. However, aligning data and workflows with these principles remains a tedious and challenging task. While metadata and paradata are well-known cornerstones for data scientists, they are frequently undervalued by data providers. This persistent gap between data providers (e.g. engineers, archaeologists) and users (e.g. curators, archivists) stems largely from the complexity of creating semantically rich documentation. Because of a steep learning curve, field experts often prioritize immediate operational tasks over long-term data usability—effectively sidelining metadata and paradata, despite their critical role in sustaining data lifecycle.

To bridge this gap, we introduce a practitioner-centric framework for metadata enrichment, paired with an open-source web application designed to lower the barrier to semantically rich documentation.

### 1.2 Research goal

Our approach is grounded in the W7 model, introduced by Ram and Liu (Ram and Liu, 2008, Ram and Liu, 2009, Liu and Ram, 2017) as a semiotic framework to enhance data provenance. The W7 model provides an intuitive and flexible semantic structure to organize metadata, effectively bridging the gap between data providers (e.g. CH practitioners) and data users (e.g. scholars, data scientists). Unlike complex metadata standards, the W7 model is accessible to all, as it relies on answering seven fundamental questions about interconnected concepts: Object (WHAT), Space (WHERE), Time (WHEN), Agent (WHO), Method (HOW), Instrument (WHICH) and Context (WHY) as shown in Fig. 1. While the W7 model's simplicity is its strength, it also presents a limitation: it is neither a formal metadata schema nor a high-level ontological framework. However, this very characteristic enables it to facilitate dialogue between low-level and high-level semantic enrichment. Since 2022, the W7 model has been applied in Cultural Heritage (CH) and Heritage Science (HS) practices, demonstrating its versatility and adaptability across various scientific domains (see section 2.1). Cultural Heritage Science (CHS) practices are not inherently FAIR-compliant, and adopting open-science principles requires a paradigm shift. Currently, documenting research protocols and digital activities is often perceived as an additional burden, leading to its avoidance or neglect. Without user-friendly tools that anticipate minimal semantic structuring, documentation is frequently sidelined. The FAIR principles, particularly the reusability pillar, introduce significant constraints for existing and future data, emphasizing the
need for enhanced provenance and traceability. Scientific
communities, including CHS and SSH, have access to nu-
merous semantic frameworks (ontologies, thesauri, con-
trolled vocabularies, and metadata schemas). However,
these frameworks are often disconnected from practitioner-
ers' needs and experiences. Mastering semantic integ-
ration requires expertise comparable to that needed for
instrumental, computational, or analytical techniques.
For reproducibility and repeatability, data lineage must
be supported by workflow management, tracking, and
provenance. The primary objective of this research is to
strike a balance between the realities of scattered prac-
tices and the theoretical constraints of semantic struc-
tures, enabling fine-grained documentation of digitiza-
tion activities.

Our hypothesis is that the paradigm shift toward FAIR-
by-design approaches is twofold. First, it involves em-
powering practitioners by providing an interfacing tool
that enhances accessibility and awareness of metadata
management, built upon a versatile framework tailored
to their needs. Second, it aims to use this tool as a
semantic bridge, centralizing user-structured document-
ation to facilitate curation and enable alignment with
broader semantic frameworks (e.g. metadata schemes,
reference models, ontologies), thereby ensuring interoper-
erability and long-term reusability.

<figure><img src="image_2.png" /><figcaption>Figure 1. Diagram of W7 model describing CHS digitization activities.</figcaption></figure>

## 2. State of the art

2.1 Related works

The MAP CNRS inherits decades of research work in ICT application to CHS documentation framework. Our research unit has been exploring the semantic enrichment of 3D modeling since 2000's (Blaise and Dudek, 2002) that one could consider today as the early stage of semantically enriched 3D digital model. Since then, the construction of Heritage Digital Twin (HDT) from a technical and methodological point of view has evolved by different means, with them the workflows to fill the knowledge gap between a static resource (text, 2D or 3D data) and correlated multidimensional data corpus (real based and parametric based 4D model enriched with semantic layers (Roussel et al., 2025)). The foundation of such semantically enriched models was achieved by the anticipation of two aspects ; the underlying semantic layers and reinforced data provenance of any modeling activity (Guillem et al., 2025). Our laboratory explored the semantic enrichment of 2D/3D models by two approaches, i) by spatial annotations (cf. Aioli platform) ii) by metadata and paradata framework. This work focuses on the second approach.

In addition to this innovative approach to convey geomet-
ric and semantic modeling methods, a reflexive approach
regarding research protocol management, has been con-
ducted. Memoria is an IS developed since 2007 specific-
ally to contribute to a formal and sharable elicitation of
research workflows (Dudek and Blaise, 2023). Activit-
ies are distributed in five goal-oriented groups dedicated
to: data collection and acquisition [78 activities], data
filtering and treatement [44 activities], data analysis [51
activities], added value procedural activities [56 activit-
ies], and finalisation [68 activities]. These 310 activit-
ies are associated with descriptors allowing a multi-level
specification of the nature of a given activity (Dudek et
al., 2022). The principles and experiences of Memoria
remain valid and inspiring despite a granularity gap to
facilitate users's adoption. Lately another complement-
ary prototype has been developed; it took the form of
an open-source web-application with an intuitive UI/UX
aiming to induce an early metadata enrichment practice.

## 2.2 Data and workflow provenance in CHS

Data provenance in CHS domains is a recurring yet un-
resolved issue. One of the first requirements to maintain
traceability is metadata, for which the community could
choose between several standardized schemes (Green-
berg, 2005), such as LIDO (Pitzalis et al., 2011),
CARARE, or more recently EDM (Isaac and et Al.,
2025), until today without a consensual adoption (Skin-
ner, 2014). This first necessary step is followed by
more complex framework (Doerr and et Al., 2014) lead-
ing to conceptual modeling to be fitted on top of real-
based modeling (Carboni and et Al., 2016, Lauro and
Lombardo, 2025). The theoretical reference model for
CH application, to be named, the CIDOC-CRM has
evolved with the practices over the time to encompass
digital activities (CRM-Dig), conservation and restor-
ation intervention (CRM-Rp) and move toward HDT
Ontology (Theodoridou and et Al., 2025). Nowadays,
it requires the accumulation of several semantic lay-
ers to overlay semantically enriched documentation of
digitization-based studies (Kuroczyński et al., 2024).
The trend is toward a standardization of CH practices,
which are, in essence — singularity of CH object re-
quires context tailored methods — and by experience
unstandardized. The main difficulty is conciliating this
multifaceted issue (i.e. FAIR approaches, data proven-
ance, workflow traceability and scientific reproductib-
ility (Massari et al., 2025)) and coping it with user-
oriented methods. Indeed the orchestration of sever-
als ontological level remains expert computer scientist
skills not to be confused with Cultural and Heritage sci-
entist (Belhajjame and et Al., 2015). Nowadays cur-
rent practices implies a tedious data curation to reach
FAIR compliance (Thomas and Brochu, 2022). Metadata
are often consider as late enrichment method (e.g. at
archival step only (Steiner and Koch, 2015)) while it
should be a dynamic approach from the source to the
output (Samuel and König-Ries, 2022) and beyond dis-
semination or storytelling (Barzaghi et al., 2025).

While Electronic Lab Notebooks (ELNs) are widely
adopted in fields like microbiology, organic chemistry,
and quantum physics for traceability and reproducibil-
ity (Mitchell and et Al., 2022), their use remains marginal
in Social Sciences and Humanities (SSH) and Cultural
Heritage Science (CHS). Existing platforms, such as the
cloud-based eLabFTW, are tailored to experimental sci-
ences and fail to meet the unique documentation needs of
CHS—requiring significant adaptation for direct applic-
ation. Despite their potential for documenting research
provenance and workflow lineage (Schröder and et Al.,
2022), ELNs have yet to gain traction in domains where
documentation practices differ fundamentally from those
in applied sciences. An attempt has been made to trans-
pose ELN for CH resource management (Schroer and
Mudge, 2017), providing a tool dedicated to image-based
documentation. While there are many solutions for CH
data management, visualization and sharing, there is a
lack of solutions to centralize metadata (Spettu et al.,
2024). In this context, W7 approaches have already
shown results to fill this gap in other domain (Arora
et al., 2019) or in web-semantic (Orlandi et al., 2010).
The W7 is an operational projection of the categories
of Bunge's high-level ontology toward documentary use,
making it compliant with other semantic layers.

3. ANAMNESIS Web-Platform

ANAMNESIS is a web application designed to man-
age metadata and paradata using W7-structured forms.
Users are guided to describe their digital activities and
resources by answering seven simple questions, which
lead to the completion of a metadata form called MEMoS
(see Fig. 2). The platform aims to document digitization
activities, complementing descriptions of the physical ob-
ject and its associated data with additional paradata.

The WHAT section describes the object of study (ma-
terial entity) and its digital version (digital entity) as
shown in Fig. 3. The WHERE and WHEN sections
describe the spatial and temporal context of the activ-
ity. The WHO section details the agents and institu-
tions involved. The WHY section provides contextual
information, such as projects and funding sources. These
first 5Ws are stabilized using Persistent Identifiers (PIDs)
connected via APIs with other services (Geonames, OR-
CID, CORDIS, etc.) as illustrated in Fig.4. The last
2Ws, HOW and WHICH, then specify the techniques
performed and the instruments used in digitization activ-
ities. These sections can be created and modified directly
in the platform's graphical interface or imported using
documented JSON schemas to allow the implementa-
tion or updating of technical schemes. The current tem-
plates already enable the documentation of workflows for
the most commonly used imaging techniques in Cultural
Heritage, such as photogrammetry, lasergrammetry, and
computational imaging (RTI, Technical Photography),
while documentation for other techniques (Infrared Ther-
mography, Climate Monitoring, Sampling, etc.) is in
the prototyping phase. Currently, most of the available
schemas (±50%) are devoted to the instrumentation and
data acquisition phase.

By organizing and sharing their metadata through the
platform, users not only adhere to best practices on
a cumulative and collaborative scale but also contrib-
ute to a centralized ecosystem—pooling activities, loc-
ations, stakeholders, and protocols. The platform fur-
ther supports this process by enabling the management

and sharing of custom templates and tools (e.g. pre-
filled forms for batch processing), fostering effortless doc-
umentation and collective enrichment. This creates a
new paradigm for scientific exploration and serendipity.
To support this, ANAMNESIS includes a shared col-
lection system, enabling easy centralization, grouping,
and dissemination of practices, entities, or reference re-
sources—alongside any form of scientific communication,
whether formal or informal. This article explains the
construction of these schemes to encourage contributions
from experienced users. User adoption is supported by
graphical and wiki-based documentation, already avail-
able online (see link below). The documentation of the
W7-ANAMNESIS schemes, including multilingual sup-
port, is managed by controlled vocabulary tools Open-
Theso, which provide comprehensive definitions and sta-
bilized URIs for interoperability purposes.

From a technical standpoint, the ANAMNESIS web ser-
vice is open-source (GNU AGPLv3 license). The backend
uses a SQLite database, which, despite its limitations,
communicates efficiently with the frontend through API-
based requests. The UI is developed using the Vue.js
framework and supports multiple languages. The UX
adopts a minimalist design (see Fig. 2) to ease metadata
input, replacing cumbersome HTML forms with an ef-
ficient, user-centric interface. The deployment of the
web application, currently hosted on the ESPADON
distributed infrastructure, is based on containerization
(Docker), anticipating multiple instances and scalability
management. The platform can also be installed locally
for use as a stand-alone application. All the resources are
available following this link : https://hnurl.fr/ccw17d.

<figure><img src="image_3.png" /><figcaption>Figure 2. Screenshot of ANAMNESIS UI showing a filled
MEMoS form.</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>Figure 3. Detailed view of the W7 WHAT section, including all entry fields and their expected values (with definitions).</figcaption></figure>

## 4. Application to CH Digitization workflow management and tracking

Using ANAMNESIS as documentation framework help practionners to structure their activities with flexible yet homogenous schemes. The already schemes implemented within the platform enable to reinforce data provenance of digitization workflow, from raw data toward the dissemination of enriched digital models. Past and current digitization practices are composed of instrumental, computational and analytical phases toward deliverable in multiple forms (e.g. scientific publication, dataset, exhibition, storytelling etc). ANAMNESIS enable to document this data stream with dedicating schemes for each category of activity in data acquisition, processing and analysis to complete the input/output operative chain. In this results and discussions section, the main activities and schemes are presented in subsection 4.1 and first outcomes are given in subection 4.2 from a pilot case studies and on-going collaboration with practionners of other imaging and measurment techniques.

### 4.1 Structuring and Linking Digitization Activities

#### Data Acquisition Schemes for Instrumental Phases:

A digitization practice begins with a data acquisition step, guided by established protocols and best practices for each technique, as well as shaped by user experience and expertise in defining the correct protocol and parameterization. During this instrumental phase, multiple choices are made, but many of these details are often omitted from technical metadata (e.g. photogrammetric baseline vs. EXIF). The technical scheme for real-based modeling enables documentation of critical aspects such as lighting, filtering, referencing, or pre-calibration

setups. This information is typically undocumented and lost in current practices, despite its well-known impact on data quality, uncertainty, and reliability. W7 schemes enable precise documentation of how data have been collected and which instruments were used, and link this information to other provenance details (e.g. operators and affiliations, research context, time-span). Such paradata, though critical for long-term archiving, open-access deposits, and data papers, are often lost during the data lifecycle.

#### Data processing schemes for computational phases:

The activity category related to processing enables documentation of computational phases, taking as input the output of a data acquisition *MEMoS* sharing a material entity and created new digital entities. Linked to the prior step, these schemes are dedicated to specifying the outputs of technical processes and methods. The examples provided in the platform include photogrammetric and lasergrammetric processing schemes. The image-based 3D reconstruction workflow has been implemented from a report generated by a processing software. It structures the main parameters for Structure from Motion (image matching and pose estimation), spatial referencing, dense matching (depth maps, optimization, etc.), and specifies options for each generated output (point cloud, mesh, texture, DEM, orthophoto). The lasergrammetric processing scheme includes registration approaches and sampling methods. The main outcome of these processing schemes is to keep track of quality control and uncertainty aspects that could impact data (re)use. This step should be seen as an intermediate phase, leading to the next stage of the workflow.
<figure><img src="image_5.png" /><figcaption>Figure 4. Overview of the core W5 sections, highlighting fields linked to Persistent Identifiers (PIDs).</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Figure 5. Example of a completed MEMoS using the photogrammetric acquisition scheme.</figcaption></figure>
**Data analysis schemes for analytical phases:**

The data generated by the digitization pipeline can serve as the source for an analytical phase. Activities in this category include data fusion, enrichment, classification, segmentation, or multi-layer visualization. Unlike previous steps in the workflow, analysis activities are expertise-driven methods and are thus more challenging to categorize and structure into metadata schemes. An attempt has been made to formalize two approaches based on internal experience. Even tough the proposed scheme were curated manually, an exploratory approach involves extracting W7 schemes from scientific publications using fine-tuned Large Language Models (LLMs). The first example is the 2D to 3D spatial annotation process, based on experiments using the AIOLI collaborative platform (Roussel et al., 2025). This schema aims to transcribe the practice of 2D/3D enrichment by synthesizing semantic structure and features (e.g. number and type of layers, number and typology of annotations, descriptors, and use of controlled vocabulary). The second example is a data fusion approach derived from an experiment to build an enhancement feature from multi-source data (Pamart et al., 2023). This schema can be reused for any data co-registration approach with advanced feature descriptions.

**Other schemes for delivering phases:**

Finally, a miscellaneous category has been implemented to include complementary steps or activities that do not fit conventional workflows. This category is more prospective but anticipates further use and advanced practices. The envisioned activities in this category are two-fold. The first involves advanced data curation and interoperable mapping, aiming to project data into open and FAIR practices. A schema is currently under construction for depositing a massive data collection into an open repository (e.g. data warehouse or data lake), requiring strictly curated metadata. A similar approach is foreseen to foster data compliance for the connection to federated knowledge graphs. These schemes can be seen as structures synthesizing the data stream, compiling and organizing all activities composing a workflow and all semantic layers added in a data collection. The second use of this special category is the metadata consolidation of innovative tools and instruments, such as smart devices and IoT sensors, hybridizing instrumental, computational, and analytical processes simultaneously (De Luca et al., 2026).

## 4.2 Case studies and examples

In order to demonstrate the practical use of ANAMNESIS, this subsection will present a amplified case-study and an on-going work to implement new schemes with expert validation.

**Using Anamnesis to document multimodal digitization practices:**

A small chapel in south of east of France has been documented among several digitization campaigns during the past decade creating a multisource digital model aiming to support further investigation for conservation and restoration purposes. For the instrumentation, the several surveys data performed by range-based and image-based techniques were documented using W7 schemes

for photogrammetry and lasergrammetry (see Fig.5). It provides an historic overview of the digitization campaign revealing the operations of many experts applying imaging techniques on different part of the chapel belonging to different research contexts. Such provenance information with enriched paradata are usually difficult to retrieve if not lost in current digitization practices. Each source was processed using conventional IBM or RBM and documented with schemes tailored for data processing providing all traceability information from a practical point of view to retrieve co-registration approach and spatial overlapping between the source. Finally, these outputs were compiled into a single digital model enriched with a fusion index documented with an ad-hoc analysis scheme. This data fusion activity summarized the enhancement features in synthetic form providing fast and efficient access of analytical procedure. Once implemented in the Misc category, a additional archiving schema could be use retrospectively to expose the structure of the data set available in a open-data repository. This complete documentation framework compose a collection of MEMoS accessible within ANAMNESIS using a UUID centralizing all the resources available on this case-study.

**Using ANAMNESIS as pivotal interface to structure W7 scheme for CH activities:**

The beta testing phase among partners positioned ANAMNESIS not only as an efficient user-oriented metadata management system but also pivotal tool to induce metadata awareness among various CHS practitioners. The initial schemes concerning common shared practices like photogrammetry and lasergrammetry presented to beta-testers picked their interest and curiosity to implement new schemes for their own techniques. Indeed, the current limitation is that a new activity or technique requires a schema for being documented within ANAMNESIS. Two approaches are currently explored to bridge this gap. The first one, is a dialogue with expert to help them formalizing their schemes for which the W7 intuitivity has been proven really helpful. Next step will focus on Competency Questions to derive from ad-hoc dialogue to procedural and stabilized routine for new scheme implementation. In the administrator panel, the platform's graphical interface the user to construct and organize themselves the new schemes of activity. Interestingly we discover that W7 is flexible enough to adapt at different levels ; not only at activities and techniques scales but also for projects, institutions, partnerships. The second one is a generalization approach targeting generic schemes even tough reaching such high-level of abstraction is challenging.

In order to ease the management of metadata schemes, we rely on Opentheso thesaurus manager to source the explanation of terminologies with a precise and expert qualification of the latter from the outset (see link given above in section 3). Indeed, although the initial schemes reflect specific in-house practices, efforts are now underway to engage partner institutions and colleagues—who explore similar subjects using diverse techniques—in order to broaden the framework’s applicability and relevance. For example, the Sampling and Climate monitoring schemes are currently being validated by the expert, as part of a joint effort with a dedicated working
group (Cormier et al., 2024) of the Espadon equipEx. Starting from undocumented practice and gray literature specific to this expertise field, the user-friendlyness of ANAMNESIS and W7 framework simplified the structuration of a metadata schema from scratch. From this experience a user documentation package has been initiated (see link given above in section 3) aiming to autonomize practitioners schemes creation and implementation.

## 4.3 Future works

From a technical standpoint, ANAMNESIS—though fully operational as a web application—remains a first-release research prototype. Minor bugs and optimizations require attention, and planned features (e.g. a metadata inspector, import tool to auto-fill existing information like EXIF data) are already prioritized in the development roadmap. From a methodological perspective, while the W7 model offers versatility, it remains underutilized CHS. Future work includes standardizing W7 as a stabilized schema using existing frameworks (e.g. schema.org, Ontoportal) to address interoperability challenges that will meet the previous point with on-going API development. Although recent studies (Guillem et al., 2025) demonstrate W7’s compliance with ontological layers (e.g. CIDOC-CRM, PROV-O) for data provenance, mapping with other metadata schemes (GoTriple, EDM, Dublin Core, DataCite) is a priority. Currently, ANAMNESIS+W7 relies on bottom-up, expert-driven creation and validation. To complement this, a top-down approach—using AI to extract metadata, schemas, and workflows from reports or articles—will be explored. Collaborations with the GRAPHIA project will leverage fine-tuned models, RAG (Retrieval-Augmented Generation), and chatbots to document techniques lacking dedicated schemas (e.g. point-based, spectral, or hyperspectral imaging in HS) or other activities in SSH/Digital Humanities. ANAMNESIS is set to be integrated into the E-RIHS Catalogue of Services as an innovative DIGILAB tool.

## 5. Conclusion

In this paper, we demonstrated how the W7 semantic framework can effectively document and preserve digitization workflows, initially applied to 2D/3D imaging but extensible to broader CHS practices. We introduced ANAMNESIS, an open-source, user-centered platform already operational for CH practitioners, offering non-rigid but structured schemas to describe common 2D/3D digitization activities. The platform stabilizes workflow documentation by centralizing and linking multiple PID layers (UUIDs, URIs, ARKs, and DOIs), ensuring traceability and interoperability. To streamline metadata and paradata documentation, ANAMNESIS provides customizable templates for data acquisition, processing, and analysis stages. This work contributes to promoting the W7 framework, with real-case CH studies illustrating its practical benefits toward reinforced data provenance workflows. We encourage experts to enrich existing schemas or create new ones based on their domain-specific needs. Ultimately, this approach aims to structure and reveal shared activities, fostering FAIR-

by-design in Cultural Heritage Sciences and beyond, with potential for cross-domain applications.

## Acknowledgements

The ANAMNESIS platform benefited from State aid managed by the Agence Nationale de la Recherche (French National Research Agency) and supported by the Paris Seine Graduate School Humanities, Creation, Heritage, Investissement d'Avenir ANR-17-EURE-0021 - Fondation for cultural heritage sciences. This project has been supported by the EquipEx+ ESPADON bearing the reference ANR-21-ESRE-0050 for the deployment and the hosting of the platform. Additional funding was provided by the CNRS through the MITI interdisciplinary programs (TEATIME) for source code improvement and optimization. This work is supported in the context of the EU-funded INFRATECH GRAPHIA project funded by the European Union Grant agreement ID: 101188018, as part of WP3 task 3.2 for the cataloguing of Innovative Workflows for Data Management and Connection to the SSH-KG.

## Roles and contributions

Contributors: Anthony Pamart (AP), Quentin Vogel (QV), Eloi Gattet (EG), Daouda Ngom (DN), Laurent Bergerot (LB). CRediT (https://credit.niso.org/): Conceptualization: AP; Data curation: AP, QV; Funding acquisition: AP; Investigation: AP; Methodology: AP, QV; Project administration: AP; Resources: AP, QV, EG, DN, LB; Software: EG, DN, LB; Supervision: AP, QV; Validation: AP, QV, EG, DN; Visualization: AP, QV; Writing—original draft: AP, QV; Writing—review & editing: AP, QV.

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