by Admin | Feb 12, 2026 | Hereditary
On 5–6 February 2026, the HEREDITARY consortium gathered at Universidade Nova de Lisboa (UNL), Portugal, for its 5th Plenary Meeting and the first in-person meeting of the project’s third year. Over two intensive days, partners reviewed progress, aligned on strategic priorities, and advanced key technical developments that will shape the next phase of the project.
The meeting followed directly after the Federated Learning Workshop (3–4 February), creating strong momentum around HEREDITARY’s core mission: enabling privacy-preserving, multimodal data analysis across European medical centres.
Opening the meeting, Project Coordinator Gianmaria Silvello (UNIPD) provided a comprehensive overview of the project’s current status. With the first review completed and 41 Deliverables successfully delivered, the consortium is now fully focused on addressing reviewers’ recommendations and consolidating technical achievements into high-impact results.
Throughout the first day, each Work Package presented its latest developments and next steps, demonstrating strong cross-WP integration and alignment with the project’s strategic objectives. The review of ongoing activities confirmed steady technical progress across data infrastructure, semantic integration, analytics, visualization, legal frameworkandcitizen science, which reinforces the coordination between clinical, technical, social and legal dimensions.
A central highlight of the meeting was the Federated Learning and Federated Analytics sessions. On the second day, SURF reported on the Federated Learning workshop and the evolution of infrastructure leadership. Discussions explored the idea of creating a living document to guide institutions in setting up secure federated learning environments. On the Federated Analytics side, the Hereditary Data Network (HDN) architecture and deployment roadmap were presented by UNIPD, ensuring a real HDN query system running by December 2026, with a clear maintenance plan, and preparing a demonstrator for reviewers in early 2027. These developments mark a decisive step towards operational federated workflow execution across heterogeneous clinical and genomic datasets.
After this, the five HEREDITARY use cases were reviewed in detail, with particular emphasis on: data storage and sources clarification, strengthening the causal interpretation of results and ensuring robust legal alignment. The consortium reaffirmed that clinical relevance and methodological rigour must be a cenral topic in the project.
Looking Ahead
With federated learning infrastructure maturing, HDN endpoints being installed, FAIRification progressing, and use cases consolidating clinical relevance, the consortium is moving decisively towards delivering a scalable, privacy-preserving framework for multimodal health data analysis in Europe.
The meeting concluded with a clear set of next action points:
- Online Plenary Meeting planned for June 2026.
- Steering Committee meeting planned for April 2026.
- Federated Learning Workshop at AAU (May 2026).
- CLEF participation registration open unil 23 April 2026.
The next two years will be key to the project’s results and impact, and HEREDITARY is aligned, coordinated and ready. Check out some photos from the event here:
by Admin | Feb 2, 2026 | Hereditary
Over the past few months, HEREDITARY has released a new series of 10 interviews on its YouTube channel, offering an inside look at the ongoing work and structure within the project. Recorded during the HEREDITARY consortium meeting held in Barcelona back in February 2025, this series brings together project partners who share insights into their own expertise and role as Work Packages Leaders, in order to explore and understand the scope of HEREDITARY’s activities.
The series includes seven interviews dedicated to the HEREDITARY Work Packages, in which consortium members explain their objectives, challenges and the main tasks currently under development. In addition, the series features three complementary interviews focusing on some key topics: Self-Supervised Learning, Visualization Techniques, and the European Health Data Space and the AI Act in the European context. Together, these videos provide a broader perspective on the methodological, technological, health-releated and regulatory aspects surrounding HEREDITARY’s research.
Below you can find the full list of interviews included in this series.
WP1 – Project Management
Giorgio Maria Di Nunzio (Università di Padova) explains how WP1 coordinates the HEREDITARY project, overseeing general, technical, ethics & risks, and data management to ensure the project progresses efficiently and ethically.
WP2 – Clinical Use Cases and Federated Networking Infrastructure
Umberto Manera (University of Turin) discusses WP2’s federated learning approach to analyze sensitive medical data and its five use cases covering ALS, Parkinson’s disease, and the gut-brain axis.
WP3 – Multimodal Semantic Integration Platform
Daniele Dell’Aglio (Aalborg University) presents WP3, which enables privacy-preserving data sharing across multiple data owners (such as hospitals and clinics) using knowledge graphs, ontologies, and federated methods to support analytics workflows.
WP4 – Multimodal Analytics & Learning Platform
Henning Müller and Manfredo Atzori (HES-SO Valais) describe WP4’s multimodal platform for integrating heterogeneous biomedical data, using self-supervised learning and spatio-temporal analytics to uncover new relationships.
WP5 – Visual Analytics and Interaction
Tobias Schreck (TU Graz) introduces WP5’s visual analytics platform, which combines machine learning and interactive visualizations to explore complex multimodal datasets and support decision-making.
WP6 – Citizen Science and Public Engagement
Chiara Lovati and Giuseppe Pellegrini (Observa) explain WP6’s Health Social Laboratories, which engage citizens and stakeholders to align research with real-life needs through collaborative dialogue.
WP7 – Legal, Ethical, and Regulatory Frameworks
Elisabetta Biasin (KU Leuven) highlights WP7’s role in ensuring HEREDITARY complies with privacy, data protection, AI, and security regulations throughout the project.
The Science Behind Self-Supervised Learning
Manfredo Atzori (Università di Padova) explains how self-supervised learning models extract patterns from raw multimodal biomedical data, helping identify subgroups and improve prognosis in neurodegenerative diseases.
Visualization Techniques for Multimodal Data
Tobias Schreck (TU Graz) presents HEREDITARY’s visual analytics methods, showing how integrating multiple data types into interactive platforms reveals hidden patterns and supports hypothesis generation.
European Health Data Space (EHDS) and AI Act in the European context
Lotte Cools (KU Leuven) discusses how EHDS and the AI Act shape access to health data and the use of AI in HEREDITARY, ensuring research remains innovative while legally and ethically compliant.
by Admin | Jan 29, 2026 | Events, Hereditary
DETECH 2026, the DEfinition and Term Extraction Challenge, organized as part of the HEREDITARY project, will take place on June 24, 2026, at University of Zadar, Croatia, as a hybrid satellite event of MDTT 2026, Multilingual Digital Terminology Today: Design, representation formats and management systems.
The training data for DETECH 2026 is now available in GitHub, and the challenge is officially open to participation. We welcome anyone interested in automatic term extraction, definition generation, biomedical NLP, and medical terminology to take part in the event. Teams and individual researchers can register until March 13, 2026, and start experimenting with the dataset ahead of the evaluation phase.
What is DETECH?
DETECH focuses on automatic extraction of domain-specific terms and the generation of natural language definitions for medical concepts. The 2026 edition will focus on the gut–brain interplay, offering a real-world testbed for NLP methods in gastroenterology, neuroscience, and genetics.
Challenge Tasks
The challenge features two main tasks:
- Task A – Term Extraction: Identify relevant single-word and multi-word terms from English texts on the gut–brain axis.
- Task B – Definition Generation: Create natural language definitions for the extracted concepts, using corpus-based evidence or automatic text generation techniques.
Key dates for DETECH 2026
- January 22: Training data release
- March 13: Registration deadline for participation
- March 20: Test data release
- March 27: Submission of runs
- April 7: Submission of reports
- April 15: Results announced
- April 21: Review feedback
- May 15: Camera-ready report submission
- June 15: Registration deadline for the event
- June 24: Day of the challenge
Who Can Participate?
Researchers, academics, and industry teams working in NLP, biomedical informatics, terminology, or lexicography. Each team can submit up to five runs per subtask and external resources such as pre-trained models, lexicons, or ontologies are allowed but must be properly documented. Manual runs are also accepted but will not be ranked.
Submissions & Evaluation
All submissions must include a technical report detailing the approach, experiments, and results. Reports will be peer-reviewed and published in the CEUR-WS online open-access platform, which is indexed in Scopus. Accepted papers can later be extended for submission to journals or edited volumes, providing further visibility for participants’ research.
What is MDTT 2026?
The “Multilingual Digital Terminology Today: Design, Representation Formats and Management Systems” (MDTT 2026) is the fifth international conference dedicated to the design, representation, and management of digital terminology resources. This event focuses on methods for analyzing user needs, designing and validating terminological resources, and developing effective representation formats and management systems.
Stay tuned for registration details and submission instructions, which will soon be available. We look forward to seeing you at DETECH 2026, where innovation in explainable, data-driven medical terminology meets cutting-edge NLP research!
by Admin | Jan 13, 2026 | Citizen Science and Public Engagement, Hereditary
HEREDITARY‘s ‘World Café Outcome: Priorities and Gaps’ report was released. The report captures key insights from a dynamic held on October 16, 2025, during EBC‘s . Diverse stakeholders, including researchers, healthcare professionals, innovators, individuals with lived experience, and patient organisation representatives, collaborated to identify solutions to challenges in multimodal health data integration, explainability of AI-based risk prediction models, and metadata alignment in a federated environment. Highlights include strategies for data standardisation, inclusive data collection, cross-sectoral collaboration, ethical AI tools, and balancing EU regulation processes to advance health research and inform brain health policy decisions.
Project representatives of the Harnessing Health Data Cluster had a chance to exchange views on the topics via interactive discussions, and three key insights were identified at the end of the meeting:
- Greater standardisation is needed at every stage of the data lifecycle (from data collection and analysis to sharing), along with clearer documentation of data sources.
- Providing education and training for healthcare professionals on required data elements can support standardisation and collection of high-quality, usable data.
- Empowering patients in data sharing consent processes and building awareness of underrepresented populations fosters patient inclusion in research.
Read the full outcomes of the HEREDITARY World Café in the REPORT.
by Admin | Jan 12, 2026 | Hereditary
The European Horizon Europe project HEREDITARY has successfully reached Month 24 of its execution, marking the halfway point of its four-year duration. This milestone confirms the project’s strong progress and consolidates the solid foundations laid during its first two years of activity, with major deliverables completed and progress achieved.
The end of 2025 closed with particularly positive news for the consortium. HEREDITARY successfully passed its first periodic review at Month 18, with all deliverables approved. Both the external reviewers and the Project Officer praised the high quality of the work, the coherence of the technical developments, and the overall advancement of the project in line with its ambitious objectives.
In December, the consortium reached another remarkable achievement: 14 deliverables were submitted in a single day, representing the highest delivery peak foreseen throughout the entire project. These deliverables span all core scientific and technical work packages, covering clinical use cases, federated and privacy-preserving data infrastructures, semantic integration, advanced analytics, visualisation tools, citizen engagement, project management, and exploitation and intellectual property planning. Altogether, they account for more than 400 pages of technical and scientific results, reflecting an extraordinary collective effort by all partners. At the end of the article, you can review the complete list of all the reports submitted. Check them all out in the Deliverables section of our website.
Among the key achievements at this midpoint, there are also two important milestones: the first operational version of the federated workflow execution engine, enabling secure and distributed analysis across institutions, on top of the federated data management infrastructure, and the progress in data FAIRification, strengthening the discoverability and alignment of HEREDITARY data resources with European initiatives and standards. Both can be consulted in Deliverables 3.2 and Deliverable 3.6, respectively.
Reaching Month 24 represents not only a quantitative success in terms of deliverables and milestones, but also a qualitative one. The results produced so far demonstrate that HEREDITARY is effectively advancing towards its vision of building a federated, interoperable and privacy-preserving ecosystem for the integration and analysis of multimodal health data, with a particular focus on neurodegenerative and gut–brain related disorders.
Looking ahead, the consortium enters the second half of the project with a clear roadmap. The coming period will focus on maturing core scientific contributions, integrating results across work packages, and consolidating HEREDITARY into a coherent and impactful ecosystem.
14 Deliverables Submitted at M24 (December 2025)
| Deliverable | Title | Brief description | Dissemination level |
|---|
| D1.5 | Risk Management Plan, 2nd report | Updated analysis of project risks identified after the second year of implementation, including mitigation and contingency measures. | EU Classified |
| D2.4 | Linkage and feature extraction from gut–brain, intermediate evaluation | Integrated brain–gut linkage and behavioural phenotyping to extract features for federated learning, including an intermediate evaluation at M24. | Public (PU) |
| D2.22 | UCD clinical studies documentation | Regulatory, ethical and data access documentation required for the UCD-led clinical studies, including approvals and MTAs where applicable. | Public (PU) |
| D3.2 | Federated workflow execution methods: first release | First release of the federated query execution engine, including intermediate implementations, optimisations, documentation and testing. | Public (PU) |
| D3.6 | FAIRification of participating data resources | Report on improvements in FAIRness of HEREDITARY data sources, with emphasis on discoverability and alignment with EU initiatives. | Public (PU) |
| D3.11 | Pilot of the genomics data science ontology interconversion | Pilot demonstrator of a clinical ontology conversion tool enabling interoperability with genomic and other biomedical data. | Public (PU) |
| D4.1 | KDE datasets and methods: first release | Open dataset including newly predicted links from the HEREDITARY knowledge graph using several knowledge graph embedding methods. | Public (PU) |
| D4.3 | Learning models and spatio-temporal harmonization | Design and first implementation of multimodal learning algorithms, self-supervised methods, and initial harmonisation libraries. | Public (PU) |
| D5.2 | Demonstrator of visualization components for sequences, networks, text, and high dimensional data | Software libraries implementing visualisation components for heterogeneous data types, including sequences, networks and text. | Public (PU) |
| D5.4 | Prototype of the visualization components for spatial, image, and simulation data | Prototype visualisation libraries addressing spatial data, biomedical images and simulation-based datasets. | Public (PU) |
| D5.7 | Requirement analysis and user studies: Initial results | Initial requirements analysis and early evaluation results derived from user studies of WP5 visual analytics tools. | Public (PU) |
| D5.10 | First evaluation challenge: report on the data, results, and integration with EOSC | Report on the first evaluation challenge, including datasets, results, open lab proceedings and integration within EOSC. | Public (PU) |
| D6.7 | World café outcome: Priorities and gaps | Synthesis of stakeholder perspectives collected during the World Café, identifying priorities and gaps relevant to HEREDITARY. | Public (PU) |
| D8.5 | Mid Term IPR plan | Mid-term Intellectual Property Rights plan outlining preliminary protection and exploitation strategies for project results. | Sensitive (SEN) |
Check them all in the Deliverables section of the website.
by Admin | Nov 28, 2025 | Events, Hereditary
The HEREDITARY project is launching the GutBrainIE Task #6 of the BioASQ Lab as part of the CLEF 2026 conference, to be held from September 21-24, 2026 at the Friedrich-Schiller-Universität in Jena, Germany.
The GutBrainIE is a Natural Language Processing (NLP) challenge focusing on advancing information extraction from biomedical literature. In this edition participants will be asked to develop and benchmark NLP systems capable of extracting structured knowledge from PubMed abstracts related to the gut-brain axis and its associations with Alzheimer’s disease, Parkinson’s disease, Multiple Sclerosis, Amyotrophic Lateral Sclerosis (ALS), and mental health.
Subtasks Overview
The GutBrainIE task is divided into two main subtasks. In the first task, participants are asked to identify and classify specific text spans into predefined categories, while in the second one they have to determine if a particular relationship defined between two categories holds or not.
These tasks are also divided into 4 four subtasks covering entity recognition, disambiguation, and relation extraction:
- Subtask 6.1.1 – Named Entity Recognition (NER)
Participants must identify text spans and classify them into one of 13 predefined categories, such as bacteria, chemical or microbiota.
- Subtask 6.1.2 – Named Entity Recognition and Disambiguation (NERD)
Following the Subtask 6.1.1, entity mentions must be linked to concept identifiers from selected biomedical reference resources.
- Subtask 6.2.1 – Mention-Level Relation Extraction (M-RE)
Teams must detect relations between specific entity mentions within abstracts.
- Subtask 6.2.2 – Concept-Level Relation Extraction (C-RE)
This subtask is related to the concept level, enabling systems to capture deeper knowledge connections.
Each task requires participants to submit structured tuples following clearly defined formats, with examples available in the official submission guidelines.
Growing International Participation
Interest in GutBrainIE continues to expand. Last year, 17 teams worldwide took part in entity and relation extraction challenges within BioASQ. The 2026 edition significantly extends the scope by introducing:
- A new entity linking task.
- One of the largest domain-specific relation extraction collections.
- Enhanced annotation efforts involving 10+ domain experts.
- Collaboration with 70+ trained layman annotators.
- A revised and improved dataset building upon previous editions.
Early registrants receive priority access to the training datasets, making this a valuable opportunity for research groups working on entity extraction, relation extraction, or entity disambiguation in specialized domains.
Registration for CLEF 2026 is open until April 2026!
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