Knowledge Graphs for Sustainable AI Impact
Data ecosystems such as data spaces and data lakes are a prerequisite for compliant access to data needed to exploit the potential of AI. These ecosystems can benefit from the use of Knowledge Graphs to improve semantic data discovery and interoperability and to increase the quality of provided data. Recent advances in methods and tools for building, maintaining, and querying knowledge graphs have shown impact both as enablers for better data management, data governance, sharing and exchange; as well as advanced analytics and recommendations. In this session, we will shed light on recent developments for handling the life cycle of large-scale knowledge graphs (build, maintain, query), and their applications in selected domains, emphasizing their ability to integrate heterogeneous data from diverse sources.
The session, organized by European research and innovation projects enRichMyData, STELAR, DataCloud and GraphMassivizer (see links below), will consist of talks on recent technological approaches related to the development and use of Knowledge Graphs and semantic services, exemplified by sustainable business cases, including applications in the agrifood sector and digital marketing. After the introductory talks, an expert panel, consisting of both technology and business experts will discuss the current and future impact of Knowledge Graphs in context of current AI developments.
Moderation: Inês Rito Lima, MOG Technologies
Agenda:
- Dumitru Roman, SINTEF AS: Brief intro and projects overview (DataCloud, enRichMyData, Graph-Massivizer, STELAR)
The tech approaches
- Manolis Koubarakis, National and Kapodistrian University of Athens: Knowledge Graphs for FAIR and AI-ready Data Lakes
- Peter Haase, Metaphacts: Knowledge Graphs and LLMs
- Matteo Palmonari, University Milano Bicocca: Data Enrichment with Human-in-the-loop
The business value
- Fernando Perales, JOT Internet Media: Data driven services for digital marketing pipelines
- Peter Haase, Metaphacts: Knowledge Graphs as foundational layer for trustworthy Enterprise AI Applications
Panel Discussion (ca 30 mins), moderated by Inês Rito Lima
- DataCloud: https://datacloudproject.eu
- STELAR: https://stelar-project.eu/
- enRichMyData: https://enrichmydata.eu/
- GraphMassivizer: https://graph-massivizer.eu/
Dumitru Roman’s presentation here
Manolis Koubarakis’ presentation here
Matteo Palmonari’s presentation here
Peter Haase’s “Knowledge Graphs and LLMs” presentation here
Fernando Perales’ presentation here
Peter Haase’s “Knowledge Graphs as foundational layer for trustworthy Enterprise AI Applications” presentation here
