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Keynote Lectures

Data Quality and Ethics in Cultural Heritage Knowledge Graphs
Valentina Presutti, University of Bologna, Italy, Italy

Available Soon
Ladjel Bellatreche, National Engineering School for Mechanics and Aerotechnics, France, France

Data Quality and Ethics in Cultural Heritage Knowledge Graphs

Valentina Presutti
University of Bologna, Italy

Brief Bio
Valentina is an Associate Professor of Computer Science at the University of Bologna. She is also an Associate Researcher at the Institute of Cognitive Science and Technologies of CNR and coordinator of STLab. She received her Ph.D in Computer Science at the University of Bologna (2006). Her research interests include AI, Semantic Web and Linked Data, Knowledge Extraction, Empirical Semantics, Social Robotics, Ontology and Knowledge Engineering. She coordinates the EUH2020 project Polifonia (2021-2024). She was responsible for several national and EU projects (e.g. MARIO, IKS, ArCo). During her post-doc she worked in NeOn and created ontologydesignpatterns.org and the series WOP, reference resources for semantic web researchers. She has published +150 peer reviewed articles. She is part of the editorial board of J. of Web Semantics (Elsevier), Data Intelligence (MIT Press), JASIST (Wiley), Intelligenza Artificiale (IOS Press), and of "Semantic Web Studies" (IOS Press). She is co-director of International Semantic Web Research Summer School (ISWS) and has served in organisational and scientific roles for several events. Google Profile - https://scholar.google.com/citations?user=dvNHkAwAAAAJ&hl=en

Abstract
Digital cultural heritage risks turning into a distorted echo of the past, built on fragmented and biased data. This keynote argues that ensuring data quality is not merely a technical challenge, but an ethical responsibility: Knowledge Graphs (KGs) that represent our heritage actively shape historical narratives and influence the reliability of AI systems. The talk will highlight both the technical and ethical dimensions of this issue, focusing on challenges such as data heterogeneity and cultural bias. Drawing on examples from our research, such as ArCo, the KG of Italian Cultural Heritage, and ChoCo, a KG integrating musical harmony datasets, I will illustrate practical methodologies to enhance data quality, while also exposing their limits and pointing to open research challenges that demand attention.

Available Soon

Ladjel Bellatreche
National Engineering School for Mechanics and Aerotechnics, France

Brief Bio
Available Soon

Abstract
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