Abstract

Abstract

Abstract
The European Union (EU) Digital Services Act (DSA) has introduced a novel set of rules for online platforms and search engines, with significant implications for the Recommender Systems community. Through its data access mechanisms, the DSA invites researchers to request both publicly available and private data from Very Large Online Platforms (VLOPs) and Very Large Search Engines (VLOSEs) - those with more than 45 million active recipients in the EU - to investigate systemic risks associated with the dissemination of illegal content, risks to the exercise of fundamental rights, and negative effects on electoral processes, public health, and gender-based violence. This tutorial is aimed at researchers who are interested in submitting such data access requests and will provide them with the knowledge to do so by introducing the relevant definitions and provisions of the DSA, and addressing the most important procedural steps to obtain data access and will provide attendees with a comprehensive understanding of the DSA's data access implications for RecSys research. The tutorial targets researchers, practitioners, and students in understanding current developments in online platform regulation in Europe and their impact on RecSys research.

Abstract
The Digital Services Act (DSA) establishes a regulatory framework for online platforms and search engines in the European Union, focusing on mitigating systemic risks such as illegal content dissemination, fundamental rights violations, and impacts on electoral processes, public health, and gender-based violence. Very Large Online Platforms (VLOPs) and Very Large Search Engines (VLOSEs), defined as those with over 45 million active recipients, must provide data access for research to enable investigations into these risks and the development of solutions. This tutorial is tailored for the UMAP community, addressing the implications of the DSA for user modelling research. It will cover the DSA's key provisions and definitions, outline the procedural steps for accessing VLOP and VLOSE data, and discuss the technical aspects of data access requests. Participants will also explore the challenges and opportunities involved in working with this data. By the end of the tutorial, attendees will have a thorough understanding of the DSA's data access provisions, the technical and procedural requirements for accessing VLOP and VLOSE data, and the regulation's implications for user modelling research. They will be equipped to navigate the complexities of the DSA and contribute to the development of responsible and transparent online platforms.Further information and resources about the tutorial are available on the website: https://erasmopurif.com/tutorial-dsa-umap25/.

Abstract

Abstract
Accurate power forecasting from renewable energy sources (RES) is crucial for integrating additional RES capacity into the power system and realizing sustainability goals. This work emphasizes the importance of integrating decentralized spatio-temporal data into forecasting models. However, decentralized data ownership presents a critical obstacle to the success of such spatio-temporal models, and incentive mechanisms to foster data-sharing need to be considered. The main contributions are a) a comparative analysis of the forecasting models, advocating for efficient and interpretable spline LASSO regression models, and b) a bidding mechanism within the data/analytics market to ensure fair compensation for data providers and enable both buyers and sellers to express their data price requirements. Furthermore, an incentive mechanism for time series forecasting is proposed, effectively incorporating price constraints and preventing redundant feature allocation. Results show significant accuracy improvements and potential monetary gains for data sellers. For wind power data, an average root mean squared error improvement of over 10% was achieved by comparing forecasts generated by the proposal with locally generated ones.