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Schedule

The final version of the program can now also be downloaded here.

Schedule Monday 09.10

Schedule Tuesday 10.10

Schedule Wednesday  11.10

Keynotes 

Erhard Rahm (University of Leipzig)

Title: Data integration for Knowledge Graphs

Abstract: Knowledge graphs (KG) have become a popular approach to semantically integrate heterogenous information within a domain or across domains. There are also vital for improved AI and machine learning.  The construction and continuous maintenance of  KGs is challenging and involves several interrelated data cleaning, data integration and knowledge refinement tasks. In the first part of the talk we give an overview about the state of current approaches for  KG construction. We then discuss data integration for KGs in more detail, in particular KG matching and incremental entity resolution. We also discuss open research problems for KG construction and data integration.

CV: Erhard Rahm is a professor of databases at Leipzig University and director of the national Data science and AI center ScaDS.AI Dresden/Leipzig. He is also vice president of the German Informatics society (GI) and a member of the DFG review board for computer science. His research interests are in the areas of data integration, graph analytics and technologies preserving data privacy. He is the author of several books and over 300 peer-reviewed publications. He received the VLDB Ten-Year  Best Paper and ICDE Influential Paper awards.

Michael Granitzer (University of Passau)

Title: OpenWebSearch.eu - Building an Open Web Index for an open web search ecosystem

Abstract: Web search has become an essential technology forming the backbone of our digital economy. A rather small number of gatekeepers dominate Web search, which creates a biased, one-sided information access centred around economic success. This one-sided ecosystem puts pressure on small contributors requiring them to optimize their content towards these gatekeeper; a vicious cycle resulting in locked-in effects and a closed search engine ecosystem.

In this talk, I will  present the recently started OpenWebSearch.eu initiative, which aims on developing an  Open Web Index (OWI) to promote an open search engine ecosystem and to provide true choice for users. I will discuss the principal of an Open Web Index, the technical challenges for developing it and how the research community could benefit from an open web search ecosystems that enables to conduct experiments at scale.

CV: Prof. Dr. Michael Granitzer holds the Chair of Data Science at University of Passau since 2017 and was full professor for Media Computer Science at the University of Passau since 2012. His research interest is on applied machine learning, web information retrieval and natural language processing. His research interest is on applied machine learning, web information retrieval and natural language processing. He published over 250 mostly peer-reviewed publications including journal publications, book chapters and books in the above-mentioned fields. Previously, he was Scientific Director of the applied research centern “Know-Center” in Graz and assistant professor at the Knowledge Technology Institute of Graz University of Technology . He managed several nationally funded and European research projects on topics like federated search and recommender systems, linked open data, and information retrieval. Besides his research, he actively support young innovators and startups in startup programs at the University of Passau. Currently, he is the coordinator of the Horizon Europe project “OpenWebSearch.eu”.

Hannes Mühleisen (Co-Founder and CEO at DuckDB Labs)

Title: Two Tier Architectures are Anachronistic - In-Process Analytical Data Management with DuckDB

Abstract: Analytical data management systems have long been monolithic monsters far removed from the action by ancient protocols. Redesigning them to move into the application process greatly streamlines data transfer, deployment, and management. This new class of systems has a whole new class of use cases, for example in-browser or edge OLAP, running SQL queries in lambdas, and Big Data on laptops.

DuckDB is a new analytical data management system that is built for an in-process use case. DuckDB speaks SQL, is trivially integrated as a library, and uses state-of-the art query processing techniques with vectorized execution and lightweight compression. DuckDB is Free and Open Source software that is distributed under the permissive MIT license. In my talk, I will explain the rationale and design decisions behind DuckDB and describe common use cases around Business Analytics and integration with Machine Learning toolkits.

CV: Prof. Dr. Hannes Mühleisen is a creator of the DuckDB database management system and Co-founder and CEO of DuckDB Labs, a consulting company providing services around DuckDB. He is also a senior researcher of the Database Architectures group at the Centrum Wiskunde & Informatica (CWI), the Dutch national research lab for Mathematics and Computer Science in Amsterdam. Hannes is also Professor of Data Engineering at Radboud Universiteit Nijmegen. His main interest is analytical data management systems.

Dr. Dietrich Alexander Herberg 

Title: The crucial last mile: mastering the art of successful implementation

Abstract: Great concepts, valuable discussions, comprehensive learnings. And now? What will you face during practical implementation and application and how can you deal with it? - Let's talk about innovation selling and success factors for implementation.

Zur Person: https://www.linkedin.com/in/dr-dietrich-alexander-herberg/

As a manager and top management consultant, Herberg has seen many great ideas and concepts and learned how to increase the likelihood that they will be implemented and create value.