DEConomy Workshop @VLDB

I am thrilled to announce that we were awarded a slot for the 3rd Data EConomy Workshop at the prestigious International Conference on Very Large Databases, to be held in London from 1st to 5th September 2025. This will be the third edition of the workshop, which I will be honoured to co-chair with Prof. George Konstantinidis. Previous editions of the workshop took place in Seattle (2023) and Rome (2022), attached to SIGMOD/PODS and CoNext conferences.

Data is no longer viewed just as a byproduct of (business) processes, but rather as a valuable resource that can be traded, processed and used in different contexts and applications. We are witnessing an unprecedented increase in both the amount of data being collected, as well as the development of infrastructure necessary to process and share the vast amounts of collected data in new contexts. Yet the full promise of the Data Economy remains largely untapped. While large corporations capitalize on their vast data and expertise, smaller entities and emerging innovators often face barriers in accessing the necessary resources, tools, and frameworks to bring their ideas to fruition.

The DEC workshop aims at bringing together researchers, practitioners and industry stakeholders in areas of the Data Economy, ranging from Data Pricing and Monetisation, to Data Privacy, Data Provenance, Data Integration and Exchange. The goal of the workshop is to identify and address impactful research problems, describe solutions and ideas to the arising data management issues (and beyond) and novel data applications, share findings from real-world data markets and PIMs/PODs, and generate new ideas for future lines of research. Building on the two previous editions, we are aiming to promote cross-pollination of ideas between academic research centers and industry, advancing the development of practical solutions and unlocking the full potential of data-driven technologies.

Workshop website link

Call for papers at the website and at Easychair

Accepted papers:

• Yizhou Ma, Xikun Jiang,WenboWu, Zhuoqin Yang, and Luis-Daniel Ibáñez. Mixture-of-Experts based Model Market
• S. Andrés Azcoitia and Alicia Cabrero Jiménez. An Interpretable Market-based Data Price Prediction Tool.
• Hajar Baghcheband, Carlos Soares, and Luis Paulo Reis. UxV-DPN: Utility-vs-Value Data Pricing and Negotiation Mechanism in Machine Learning Data Marketplace
• Soulmaz Gheisari, Jaime Osvaldo Salas, Semih Yumusak, and George Konstantinidis. MINiDM: Multi-Issue Negotiation in Decentralised DataMarketplaces.
• Shanshan Jiang, Sondre Sørbø, Phil Tinn, Shang Ferheng Karim, and Dumitru Roman. LLMDap: LLM-based Data Profiling and Sharing.