EU-Korea Digital Partnership: From Vision to Delivery
other
15 September 2026 09:00
to
17 September 2026 18:00
(Seoul time)
The programme includes
- The EU–Korea Tech Frontier Workshop: Shaping the Digital Future Together, focused on short- and medium-term action planning for the EU–Korea Digital Partnership,
- The AI Ready Data Challenge, dedicated to field testing standards and approaches for Data Quality Metrics evaluation.
Events
EU–Korea Tech Frontier Workshop: Shaping the Digital Future Together
15 September 2026 09:30 to 18:00 (Seoul time)
Grand Central Hotel, Seoul
The EU–Korea Innovation Workshop is a high-level event bringing together European and Korean experts in 6G, Cybersecurity, Quantum technologies, and Data/AI to identify priority themes for EU–Korea research and industrial cooperation, aligned with the EU–Republic of Korea Digital Partnership.
Building on the momentum of the EU–Korea Digital Partnership, inaugurated in November 2022 and consistently expanded since, including at the 11th EU–ROK Summit in June 2026, the workshop focuses on three technology domains at the cutting edge of EU–Korea joint interest: 6G and AI-native networks, quantum computing and cryptography, and physical AI. A dedicated closing session on the INPACE Peer Advisory Network will translate the day's technical discussions into concrete cooperation pathways.
AI Ready Data Challenge
16 September 2026 09:00 to 17 September 2026 17:00 (Seoul time)The AI Ready Data Challenge is a hands-on, collaborative event bringing together dataset owners, researchers, standardisation experts, and AI practitioners to evaluate datasets against the 18 Data Quality Metrics defined in ETSI TR 104 180 and the open-source validation toolset developed in the associated Proof of Concept (PoC), hosted by Sejong University.
Participants bring their own real-world datasets and put all 18 ETSI TR 104 180 data quality metrics (Completeness, Reliability, Redundancy, Accuracy, Timeliness, Consistency, Integrity, Uniqueness, Precision, Availability, Coverage, Lineage, Anonymity, Label Quality, Traceability, Confidentiality, Measurement Bias, and Representation Bias) to the test, generating hands-on evidence. Across domains ranging from industrial IoT and AI/ML training datasets to data spaces and physical AI, participants will discover which metrics matter most for their specific use case and why.
Every result will feed directly into the future of standardisation: the empirical findings gathered during the challenge will inform the transition from TR 104 180 to a Technical Specification that will shape the next generation of standardised methods for data quality evaluation. Throughout the two days, participants get live access to an open-source Data Quality Validation tool.
Participants bring their own real-world datasets and put all 18 ETSI TR 104 180 data quality metrics (Completeness, Reliability, Redundancy, Accuracy, Timeliness, Consistency, Integrity, Uniqueness, Precision, Availability, Coverage, Lineage, Anonymity, Label Quality, Traceability, Confidentiality, Measurement Bias, and Representation Bias) to the test, generating hands-on evidence. Across domains ranging from industrial IoT and AI/ML training datasets to data spaces and physical AI, participants will discover which metrics matter most for their specific use case and why.
Every result will feed directly into the future of standardisation: the empirical findings gathered during the challenge will inform the transition from TR 104 180 to a Technical Specification that will shape the next generation of standardised methods for data quality evaluation. Throughout the two days, participants get live access to an open-source Data Quality Validation tool.