Felix Naumann

Felix Naumann studied mathematics, economy, and computer sciences at the University of Technology in Berlin and completed his PhD thesis in the area of data quality at Humboldt University of Berlin in 2000. After a PostDoc position at the IBM Almaden Research Center working on data integration topics, he came assistant professor for information integration, again at the Humboldt-University of Berlin in 2003. Since 2006 he holds the chair for Information Systems at the Hasso Plattner Institute (HPI) at the University of Potsdam in Germany. He has been visiting researcher at QCRI, AT&T Research, IBM Research, and SAP. His research interests include data profiling, data quality and cleansing, and data integration, recorded in over 200 scientific publications. Next to numerous PC memberships for international conferences, he has organized several conferences in various roles, including VLDB 2021 as PC co-chair, and he is the Editor-in-Chief of the ACM Journal of Data and Information Quality (JDIQ). More details are at https://hpi.de/naumann/people/felix-naumann.html.

Data Quality in the Age of AI

Data quality comprises a large set of dimensions, covering many facets including simple statistics, syntactic problems, factual errors, and organizational and business aspects. With the current trend in data-oriented sciences and the increasing reliance on machine learning methods and AI systems, the challenges of poor data quality are ever more apparent. Even recent legislation, such as the EU AI Act, mentions data quality requirements for training data. With it, the notion of data quality extends to novel dimensions, such as fairness, diversity, or explainability. In the talk we shall highlight research in this field and point out current challenges and research opportunities.

Data Profiling - a Primer

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Evaggelia Pitoura

Evaggelia Pitoura is a Professor at the Department of Computer Science and Engineering at the University of Ioannina and a Lead Researcher at Archimedes Research Unit of Athena RC, Greece. She holds a BEng degree from the University of Patras, Greece, and an MS and PhD from Purdue University, USA. Her current research interests focus on two primary areas: responsible data management, with a focus on fairness, explainability, and their interplay; and on graph exploration and analysis. For her work, he has received best paper awards, a Marie Currie Fellowship and two Recognition of Service Awards from ACM. She is an ACM senior member, chair of the Greek ACM-W event steering committee, chair of the Hellenic ACM SIGMOD chapter, and member of the sectorial scientific council of Greece National Council for Research, Technology and Innovation.

Diversity-Aware, Fair and Unbiased Data Management

As AI algorithms are increasingly deployed in domains that profoundly impact human lives, concerns about their fairness and transparency have become more pressing. Recently, significant attention has been directed towards the interconnection of explainability and fairness to advance responsible AI systems. Despite this growing interest, the relationship between these two concepts remains underexplored. In this talk, I will share our recent research on leveraging post-hoc explainability methods to detect and understand the root causes of biases in algorithmic outputs. Additionally, I will discuss the role of explainability in Retrieval-Augmented Generation (RAG) pipelines and highlight opportunities for data-driven research in this critical area.

Eero Hyvönen

Eero Hyvönen is professor of semantic media technology at the Aalto University, Department of Computer Science, and director of Helsinki Centre for Digital Humanities (HELDIG) at the University of Helsinki. His research has focused since 2001 on Semantic Web and Linked (Open) Data technologies, developing with his Semantic Computing Research Group (SeCo) (https://seco.cs.aalto.fi/) the national semantic web infrastructure in Finland (https://seco.cs.aalto.fi/projects/lodi4dh/) and its applications in different areas, especially in Cultural Heritage and for Digital Humanities research (https://seco.cs.aalto.fi/applications/sampo/). Eero Hyvönen has published nearly 600 articles and books and got nearly 30 international and national honorary prizes and acknowledgements.
Eero Hyvönen
[1] Eero Hyvönen: Using the Semantic Web in Digital Humanities: Shift from Data Publishing to Data-analysis and Serendipitous Knowledge Discovery. Semantic Web, vol. 11, no. 1, pp. 187-193, 2020.
[2] Eero Hyvönen: How to Create a National Cross-domain Ontology and Linked Data Infrastructure and Use It on the Semantic Web. Semantic Web, vol. 15, no. 4, pp. 1499-1513, 2024.
[3] Eero Hyvönen: Digital Humanities on the Semantic Web: Sampo Model and Portal Series. Semantic Web, vol. 14, no. 4, pp. 729-744, 2023.
[4] Eero Hyvönen: Serendipitous knowledge discovery on the Web of Wisdom based on searching and explaining interesting relations in knowledge graphs. Journal of Web Semantics, Elsevier, 2025.

Digital Humanities on the Semantic Web: from Infrastructure to Practical Applications, AI-based Knowledge Discovery, and Web of Wisdom

Publishing Cultural Heritage (CH) data and Digital Humanities (DH) has evolved in phases from text carving and handwriting to printing texts, to publishing texts on-line, to publishing FAIR linked data comprehensible to computers for data enrichment and analysis, and to AI-based knowledge discovery on the Web, a “Web of Wisdom” [1]. In this keynote, lessons learned are overviewed on developing a national Semantic Web infrastructure [2] and over 20 in-use systems based on it with up to millions of end users during 2002-2024 [3]. The underlying linked data in these applications include museum collections, bibliographical data in libraries, medieval and renaissance manuscripts, military history, biographies, narratives, historical letter data, archaeological finds, legislation, parliamentary speeches, and art. Targeted to Digital Humanities researchers, application developers, and the public, these systems contain a Linked Open Data (LOD) service with a live SPARQL endpoint that can be used with modest programming skills for DH research, and a ready-to-use semantic portal on top of it. This work has led into the so-called Sampo Model for creating and publishing CH Knowledge Graphs (KG) as LOD services and semantic portal User Interfaces (UI).

Yannis Ioannidis

Yannis Ioannidis (Ph.D., Computer Sciences, UC Berkeley; MSc, Applied Mathematics, Harvard University; Diploma, Electrical Engineering, National Technical University of Athens) is the President of the Association of Computing Machinery (ACM). He is a Professor at the Department of Informatics and Telecom of the University of Athens as well as an Associated Faculty at the “Athena” Research and Innovation Center, where he also served as the President and General Director for 10 years. His research interests include Database and Information Systems, Data Science, Data Infrastructures and Digital Repositories, Recommender Systems and Personalization, and Interactive Digital Storytelling, topics on which he has published over 180 articles in leading journals and conferences and holds four patents. His work is often inspired by and applied to data management and analysis problems that arise in industrial environments or in the context of other scientific fields (Social Sciences and Humanities, Life Sciences, Physical Sciences) and the Arts. He is an ACM and IEEE Fellow, a member of Academia Europaea, and a recipient of several research, teaching, and service awards. He is a co-founder of OpenAIRE, the international data infrastructure for Open Science in Europe, as well as of several AI/data-driven start-ups. He is also a co-chair of the Global Climate Hub of the UN Sustainable Development Solutions Network.

Interactive Digital Storytelling

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Robert Wrembel

Robert Wrembel (PhD, Dr. Habil.) is an associate professor in the Faculty of Computing and Telecommunications, at Poznan University of Technology (Poland). In 2008 he received a post-doctoral degree in computer science (habilitation), specializing in database systems and data warehouses. He has been a deputy dean of the Faculty of Computing and Management (2008–2012) and the Faculty of Computing (2012–2016). Since Jan 2023 he is the chair of the Data Processing Technologies group at Poznan University of Technology; since May 2023 he is the leader of the Interdisciplinary Centre for Artificial Intelligence and Cybersecurity in Poznań https://caics.put.poznan.pl/. He was a consultant at software house Rodan Systems (2002–2003) and a lecturer at Oracle Poland (1998–2005). Currently he is an IT consultant in hospital Centrum Medyczne HCP. Within the last 10 years he has realized four R&D projects: one for the biggest Polish bank – PKO BP, one for a company in the energy sector – Kogeneracja Zachód, and two for Samsung Electronics. He cooperates with IBM Software Lab Kraków in Poland. He has led at his University the Erasmus Mundus Joint Doctorate Program – Information Technologies for Business Intelligence – Doctoral College (2013–2020). Robert visited numerous research and education centers, including: Universitat Politècnica de Catalunya – BarcelonaTech (Catalunya), Université Lyon 2 (France), Universidad de Costa Rica (Costa Rica), Klagenfurt University (Austria), Loyola University (USA), INRIA Paris-Rocquencourt (France), and Université Paris Dauphine (France). In 2012 he graduated from a 2-month innovation and entrepreneurial program at Stanford University. In 2013 he has done an internship in a BI company Targit (USA). His research interests encompass: data integration, data quality, databases, data warehouses, and data lakes.
Webpage: http://www.cs.put.poznan.pl/rwrembel/

Data integration for Data Science

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Maribel Acosta Deibe

Maribel Acosta is the Professor of Data Engineering at the TUM Campus Heilbronn since August 2023. Maribel Acosta studied Computer Science at Universidad Simon Bolivar, Venezuela. From 2012 to 2017, she was a research assistant at the Karlsruhe Institute of Technology (KIT), where she received her doctorate. She then worked as a postdoc and deputy professor at KIT until 2020. Afterward, she was appointed as the professor for Databases and Information Systems at the Ruhr-University Bochum until July 2023. She is actively involved in the scientific communities on Data Management and Artificial Intelligence. Her work has received several “Best Paper Awards” and she serves as chair and reviewer for renowned conferences. Besides research, Maribel Acosta has many years of teaching experience in Databases, Big Data, and Knowledge Graphs and has received two “Best Teaching Awards”. Maribel Acosta investigates techniques for managing knowledge graphs. Her contributions include efficient solutions for querying knowledge graphs while providing high-quality answers.

Neuro-Symbolic Query Optimization in Knowledge Graphs

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Tania Cerquitelli

Tania Cerquitelli is a Full Professor at the Department of Control and Computer Engineering (DAUIN) of the Politecnico di Torino, Italy. Her research interests include self-learning methodologies and explainable AI techniques, the design of innovative algorithms to perform large-scale data science, novel and efficient solutions for concept-drift management, and algorithms to extract high-level abstractions of the mined knowledge (e.g., generalized patterns). Specifically, she organized nine editions of the international workshop on data analytics for real-life applications (DARLI-AP) in conjunction with EDBT/ICDT 2018 - 2025 Joint Conference and all the previous editions of the Workshop on Data Science for Equality, Inclusion and Well-being Challenges in conjunction with the IEEE Big Data conference. Tania has published over 100 scientific publications and has been a referee for many international journals. She served on the program committee of several international conferences and workshops in the data mining, data science and machine learning areas. Tania is an associate editor for different Elsevier and Springer journals.. She supervises the research activity of many graduate and PhD students. She got a master’s degree in Computer Engineering (in 2003) and a Ph.D. degree (in 2007) from Politecnico di Torino, Italy, and a master’s degree in Computer Science (in 2003) from the Universidad de las Américas Puebla.

Designing and Deploying DS Projects

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Genoveva Vargas-Solar

Genoveva Vargas-Solar is a CNRS principal scientist (exceptional class) and a member of the Database group at the LIRIS lab in France. From 2008 to 2020, she was deputy director of LAFMIA, an international research unit at CINVESTAV. A regular Mexican Academia of Computing member, she has organized numerous international conferences, workshops, and thematic schools, such as EDBT Summer Schools (2009, 2013) and the Franco-Brazilian School on Smart Cities and Big Data (2015, 2017). She has edited several conference publications and served on program committees for major journals and events in databases and service-based programming. Her research spans fundamental and applied challenges on ARM, Raspberry, cloud, and HPC architectures, applied to e-science in Astronomy, Biology, social sciences, and Industry 4.0. She has coordinated multiple international research projects and actively fosters scientific collaboration between Latin America and Europe, particularly between France and Mexico. Additionally, she is a committed advocate for gender equity, diversity, and inclusion, serving as a gender equity officer at LIRIS and coordinating initiatives like the DEI Database Conferences.

Ethical & Equitable Data Science

This 1-hour course provides a comprehensive exploration of the ethical, social, and fairness challenges in data-driven decision-making. The session begins by introducing key ethical principles, including transparency, accountability, and bias mitigation. Participants will examine real-world cases where data practices led to unintended harm, highlighting the need for responsible AI and fairness in model development.

The course will explore the broader socio-economic, environmental, and ethical implications of data science. Special attention will be given to issues of data sovereignty, fairness, and inclusivity, particularly addressing the marginalization of voices and the impact of technological monopolies. Participants will be introduced to decolonial methodologies and fairness metrics that respect cultural and contextual diversity. The course will also cover practical techniques for detecting and mitigating biases in datasets and algorithms, including algorithmic auditing and inclusive data collection practices. Additionally, attendees will gain an understanding of regulatory frameworks such as AI ethics principles, helping them navigate the legal and ethical landscape of responsible data science.

The session concludes with an exploration of best practices for building equitable and trustworthy models, empowering participants to apply ethical considerations in their own work.

Through interactive discussions and case studies, this course fosters a socially responsible approach to data science, challenging the dominance of major tech companies and advocating for sustainable and inclusive resource allocation in analytics.

Tatjana Welzer

Tatjana Welzer is Full Professor at the University of Maribor, Faculty of Electrical Engineering and Computer Science. She is the Head of the Database Technologies Laboratory of the Institute of Informatics. She received her Ph.D. in Computer Science in 1995. Her research work covers a wide range of research areas, from databases, cyber security to intercultural communication and research in education. She has participated in numerous national and international research projects funded by the European Union through various Erasmus (European University ATHENA) and H2020 programmes (CONCORDIA, CyberSec4Europe). Her bibliography contains more than 700 bibliographic items, including top JCR IF publications as well as several books. She is also an active reviewer for scientific conferences and journals. She is a member of the Senate of the Faculty of Electrical Engineering, Computer Science and Informatics (FERI) and the member of the Executive board of the Slovenian Society Informatika.

Technical writing, text typesetting, slides preparation, technical talks preparation, and public speaking

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Toni Taipalus

Toni Taipalus is a researcher and teacher at the Faculty of Information Technology, University of Jyväskylä, Finland. His research has been published in journals such as Journal of Systems and Software and ACM Transactions on Computing Education. His current research interests include query languages, database management systems, and computing education.

Vector database management systems

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