Keynotes

Knowledge Beyond Documents: FAIR Ontologies for Humans and Machines

The FAIR principles have significantly improved the publication and reuse of digital resources, promoting data that are Findable, Accessible, Interoperable, and Reusable. However, as AI-based systems increasingly consume and generate knowledge, achieving machine-actionable interoperability requires not only FAIR data but also FAIR ontologies. In this keynote, I will argue that FAIR ontologies are a cornerstone of machine-actionable knowledge. Beyond enabling semantic interoperability, they support knowledge integration, discovery, and explainability across digital infrastructures. I will present recent advances in ontology engineering, discussing practical approaches, tools, and best practices for designing and publishing FAIR ontologies, together with current challenges such as documentation, metadata, versioning, quality assessment, governance, modularity, reuse, and long-term sustainability. Ultimately, I will argue that moving from FAIR Data to FAIR Knowledge requires treating ontologies as first-class FAIR digital resources.

Temporal Intelligence in Language Technologies: Modeling, Retrieval, and Reasoning

Time is central to how we understand the world. It shapes how we interpret events, construct narratives, and reason about change, causality, and evidence. In this talk, I will first examine how well large language models handle temporal information and temporal reasoning, an essential but still less explored dimension of language intelligence. I will then discuss recent advances in incorporating temporal awareness into language technologies, including time-aware representation learning, retrieval from evolving document collections, and the development of new resources for training and evaluation. I will also introduce temporal reasoning-oriented question answering and retrieval benchmarks that highlight the challenges of retrieving time-sensitive information, answering complex temporal questions, and reasoning over changing evidence. The talk will conclude with open challenges for building language technologies that can better understand, retrieve, and reason over information across time.

From Excavation to Infrastructure: Computational Archaeology and the Rise of HeritageTec

For most of its history, archaeology has produced data faster than it can organise, share, or reuse it. Excavations, surveys, and laboratory analyses generate vast, heterogeneous records (spatial, material, biomolecular, textual) that too often remain locked in incompatible formats and inaccessible archives. This talk argues that the future of archaeological heritage depends on treating these records not as by-products of research, but as durable, interoperable infrastructure.

Drawing on two decades of computational practice, from GIS and remote sensing to machine learning and 3D reconstruction, I will trace how digital methods are reshaping the way we recover, interpret, and communicate the human past. I will then turn to UAlgTec Heritage (UTH), the first HeritageTech Centre of Excellence in Europe, which moves beyond digitisation and access toward full science-to-policy integration: converting validated research into deployable tools, FAIR- and CARE-compliant data services, and evidence for territorial planning and risk assessment. For the digital libraries community, archaeology is both a demanding test case and a natural ally. I will close by asking how the theory and practice of digital libraries can help heritage data become genuinely findable, reusable, and actionable, and what an emerging field of “HeritageTech” might offer this community in return.