 | DEC25: Data Economy Workshop 2025 Queen Elizabeth II Centre (QEII Centre) London, UK, September 5, 2025 |
| Conference website | https://sites.google.com/view/data-economy-2025/ |
| Submission link | https://easychair.org/conferences/?conf=dec25 |
| Submission deadline | June 9, 2025 |
Data-driven decision making powered by Artificial Intelligence (AI) algorithms is changing the global economy and has a profound positive impact on our daily life. With the exception of very large companies that have both the data and the skills to develop powerful AI-driven services, the large majority of provably possible ML services, from e-health, to transportation and predictive maintenance, to name just a few, still remain at the idea (or prototype) level, for the simple reason that data, the skills to manipulate them, and the business models to bring them to market, seldom co-exist under the same roof. The value of data comes from its contextualisation and combination with other data. Indeed, this can give way to many new services and products. Furthermore, data must be combined with the AI and business skills that can unleash its full power for the society and economy. This landscape has given rise to the highly dynamic sector of Data Economy, involving Data Providers/Controllers, Data Intermediaries, oftentimes in the form of Data Marketplaces or Personal Information Management Systems for end-users to control and even monetise their personal data. Despite its huge potential and observed initial growth, the Data Economy is still at its nascent phase and faces several challenges and a broad range of technical issues across multiple disciplines of Computer Science including databases, machine learning, distributed systems, security, privacy, and human-computer interaction.
The Data Economy workshop aims at bringing together all the data management and CS skills required for helping the Data Economy liftoff by addressing a range of technical challenges including, but not limited, to the ones below:
● Data management and querying in Data Marketplaces
● Design, architecture, systems and protocols for Data Marketplaces, Data Providers, Personal Online Data Stores (PODS), and Personal Information Management Systems (PIMS)
● Consent management and taxonomy of data processing purposes
● Sending the data to the algorithm vs. sending the algorithm to the data
● Federated and distributed learning in the data economy
● Heterogeneous and federated DBMS
● Federated data catalogues, metadata management and data discovery mechanisms
● Data representation and exchange standards in the data economy
● Secure data integration, exchange and delivery mechanisms
● Information Integration and Data Quality
● Privacy/data protection, data governance and the data economy
● Protecting data ownership rights for commercial datasets
● Data pricing mechanisms for individual and aggregated data
● How to buy data – data purchase policies and algorithms
● NFTs, blockchains, smart contracts and their role in the data economy
● Trusted execution, cloud computing, distributed storage and their role in the data economy
● Understanding the value of data in different applications and domains across the data value chain
● Cryptographic approaches, such as FHE, SMPC, DP, their role and limits in the data economy
● UX and HCI challenges for data marketplaces and PIMS
● Legal issues related to data marketplaces or the data economy at large
● Federation and interoperability standards and protocols in the data economy
● Measurement studies related to the data economy
● Large-scale experiments and validation studies for the data economy