The Program
08:30
Admission
- | Wandelhalle |
09:00
09:10
Keynote
- | Sitzungssaal | English
Keynote by Ben Gardner (AstraZeneca): Enabling new medicines with FAIR Data-centricity: Delivering Linked Data inside the enterprise
Ben Gardner AstraZeneca
Vita
Ben is R&D lead for Data Mesh and Semantic Infrastructure at AstraZeneca he is responsible for the application of graph technology in support of Information Discovery. He is focused on delivering FAIR Data-centric architecture to create multimodal integrated data sets to enable exploration and reuse of pre-clinical, clinical and Real World Evidence data. Ben started life as a bench scientist leading drug discovery teams. This was followed by a move into data architecture where he was responsible for the introduction of Enterprise 2.0 tools and development of knowledge management frameworks that enhanced collaboration and communication across multiple communities. Subsequent to this he lead efforts to enhance the Information Discovery capabilities across structured and unstructured information sources at Linklaters by blending AI technologies with relational and semantic data integration solutions. This was followed by a role as Chief Scientific Officer at Wavelength.law where he was responsible for the application of data science to legal process.
10:00
Coffee break
- | Wandelhalle |
Posters and Stands
10:30
Session I: Knowledge Graphs and Large Language Models
- | Sitzungssaal | English
Chair:
Kirill Bulert
(Institute for Applied Informatics)
In this session, we’ll chat about Semantic Technologies within the bigger picture of Artificial Intelligence and cool stuff like ChatGPT.
- Abhishek Nadgeri (Fraunhofer-Institut für Angewandte Informationstechnik FIT): KELLM, Knowledge-Enhanced LLMs
- Johannes Frey (Institute for Applied Informatics) and Lars-Peter Meyer (Institute for Applied Informatics): How well can LLMs “talk” with your Knowledge Graph?
- Prof. Dr. Lisa Wenige (Office for Statistics and Elections and Hochschule Merseburg): SPARQLing with AI: A Roadmap for a Family of AI-Enhanced SPARQL Custom Functions
- Prof. Dr. Felix Sasaki (SAP SE): How to make generative AI in the enterprise work with knowledge graphs: RDF, Property Graphs, or both?
- Kheir Eddine Farfar (Technische Informationsbibliothek (TIB)): Intertwining Machine Learning and Semantic Web in the Open Research Knowledge Graph
- Felix Brei (Institute for Applied Informatics): Surveying language models with less than 1B parameters for SPARQL translation
12:00
Lunch break
- | Wandelhalle |
Posters and Stands
13:00
Session II: Knowledge Graph Use Cases in Industry
- | Sitzungssaal | English
Chair:
Magnus Knuth
(eccenca GmbH)
In this session, we’ll explore real-world applications and use cases using Knowledge Graphs as our foundation.
- Hans-Christian Brockmann (eccenca GmbH): Neurosymbolic AI a billion dollar opportunity
- Nikolay Krustev (Ontotext): Industrial Knowledge Graphs in action
- Inga Glotzbach (adorsys GmbH & Co. KG): Connecting Dots: How DATEV Leverages Knowledge Graphs to Shape its Data Product Catalog
- Jeniffen Chandrabalan (RB Leipzig) and Simone Mueller (RB Leipzig): Architecting a Modern Data Stack for Commercial Analytics in Football
- Vincent Vialard (derivo GmbH): Overview first, details on demand for truly scalable Knowledge Graph exploration
- Achim Reiz (Neonto): Evaluating Knowledge Graph Quality in Practice
14:30
Coffee break
- | Wandelhalle |
Posters and Stands
15:00
Session III: Ontology Engineering and Semantic Technologies
- | Sitzungssaal | English
Chair:
Edgard Marx
In this session we will dive into the exciting world of semantic technologies and will get our hands dirty with the tools and techniques needed to make sense of complex information
- Dr.-Ing. Sebastian Hellmann (Institute for Applied Informatics): Databus: FAIR Data in Energy Systems Analysis
- Prof. Dr. Axel-Cyrille Ngonga (Paderborn University): Tentris: From Tensors to Ten X
- Dr. Natanael Arndt (German National Library): The Web Archive of the Future at the German National Library
- Lars-Peter Meyer (Institute for Applied Informatics): Project StahlDigitial – lessons learned on ontology engineering in the steel domain