GRAPHIA promotes a close collaboration model between research infrastructures (ESFRI) such as EHRI, OPERAS, RESILIENCE, and GGP, and private sector actors, notably innovative SMEs. This partnership takes shape through concrete use cases, prototypes, and shared services that address both fundamental research needs and industrial applications. The project also aims to develop new innovation workflows via prototyping labs (IPLs), accelerating the sector’s digital transformation.

Foxcub plays a central role in GRAPHIA as the technical coordinator of the project and a key partner in overseeing activities. Alongside OPERAS, we lead the inter-WP technical coordination and contribute to the overall management of the work.

On the technical side, Foxcub designs, deploys, and industrializes the project’s SSH knowledge graph. We implement enrichment pipelines, evaluate and optimize the use of open-source technologies (RDF, LPG, graph learning), and ensure their integration in cloud-based environments. We are also involved in semantic architecture, data acquisition from heterogeneous sources, and interoperability mechanisms with other European graphs.

Finally, Foxcub contributes to the development of a large-scale SSH citation index, based on advanced AI modules for extraction, disambiguation, and enrichment of references.

GRAPHIA is preparing the integration of the Social Sciences and Humanities (SSH) into future European Data Spaces. By promoting mutualization, traceability, and the openness of research data, it addresses the challenges of digital sovereignty, transparency, and responsible innovation set out in the European data strategy. The project thus helps to reposition SSH as a strategic domain for digital transformation and the competitiveness of Europe’s scientific and industrial ecosystems.

The project is based on a Data Mesh architecture that combines community platforms, each acting as a shared platform open to all. Each platform is governed by a data contract, guaranteeing semantic quality and responsible exposure of its resources. LUMEN also develops mutualized technical infrastructure with a shared set of transversal functionalities: search engines, discovery interfaces, FAIR management of semantic artefacts, monitoring dashboards, and catalogs of software and data services.

Foxcub is the technical coordinator of the LUMEN project. In this role, we ensure planning, deliverables, and overall technical consistency, in close collaboration with partners and the requirements of EOSC.

We lead the design of the Data Mesh architecture and the metamodel to facilitate interoperability between platforms. As the leader of development, we are building the FAIR platform for managing semantic artefacts, aimed at enriching data and feeding the discovery platforms with semantically aligned content.

Foxcub also contributes to the integration and improvement of open-source services and actively participates in semantic interoperability across scientific domains.

LUMEN aims to sustainably transform modes of scientific collaboration across disciplinary silos. By proposing a replicable architecture, open tools, and a model of federated governance, the project strengthens the autonomy of all communities while supporting their networking. It directly contributes to the evolution of the EOSC ecosystem by supporting concrete solutions for open science that are interoperable and sustainable.

The platform is based on Darwin Core and GBIF standards and supports many scientific references (TAXREF, GeoNames, INPN, TDWG…). It allows the publication of datasets in the Darwin Core Archive (DwC-A) format, facilitating their archiving, harvesting, and reuse in FAIR infrastructures such as GBIF.

SoL includes an interactive spectral annotation interface to precisely mark vocalizations based on frequency and time criteria. Users can enrich annotations using tags, controlled vocabularies, or hypotheses, supporting reproducibility and future automatic processing. The tool is designed to adapt to diverse user profiles (bioacousticians, ecologists, data stewards, etc.).

Foxcub leads the technical design of the platform, the development of its interfaces, the modular architecture, and the integration of FAIR standards. We also contribute to the design of the data model, import and annotation workflows, GBIF export, and the roadmap for future automatic enrichment processes (AI, classification, acoustic indexing).

Foxcub is involved in the standardization and harmonization of vocabularies used to describe and enrich metadata, ensuring semantic compatibility between platforms and supporting the circulation of enriched content. We ensure the integration of shared reference frameworks and the application of international standards to guarantee long-term interoperability.

We actively coordinate exchanges between service providers, researchers, and platforms, facilitating workshops and capacity-building to improve the quality and continuity of services and data. Foxcub also supports training and dissemination of best practices to foster digital transformation in the sector.

As part of the transformation process, the GoTriple platform performs a series of data cleaning, normalization, and enrichment procedures, to manage metadata heterogeneity, enhance multilingualism, and improve content discovery. It also stores and indexes enriched metadata records, making them accessible via the GoTriple search engine.

As part of this major European project, Foxcub was in charge of AI-based enrichments (Machine Learning / Deep Learning) to enable the automatic categorization of disciplines at the article level and semantic enrichments supporting keyword annotation.

Since its launch in 2023, GoTriple has enabled companies and public institutions to use and reuse scientific results for their own purposes, particularly to foster economic, societal, and scientific innovation.

Matilda is a shared open science tool designed for all scientific communities, based on metadata from scholarly texts, especially citation and reference data.