The RecSys Challenge 2024 aims to advance news recommendation by addressing both the technical and normative challenges inherent in designing effective and responsible recommender systems for news publishing. This paper describes the challenge, including its objectives, problem setting, and the dataset provided by the Danish news publishers Ekstra Bladet and JP/Politikens Media Group ("Ekstra Bladet"). The challenge explores the unique aspects of news recommendation, such as modeling user preferences based on behavior, accounting for the influence of the news agenda on user interests, and managing the rapid decay of news items. Additionally, the challenge embraces normative complexities, investigating the effects of recommender systems on news flow and their alignment with editorial values. We summarize the challenge setup, dataset characteristics, and evaluation metrics. Finally, we announce the winners and highlight their contributions. The dataset is available at: https://recsys.eb.dk.

Back at IBC2017 there were three workflow demos of the DPP News Exchange project promoting the sharing of metadata, and this vital work has now arrived at prototype mode, with the prospect of publication in early April along with implementation guidance. The drivers of this project are the BBC, ITV, ITN, Sky, C5, Thomson Reuters, Sony, Avid, Telestream, Scisys, IPTC, and SAM (now Grass Valley). Confirming that a compliance program will also follow publication, Andy Wilson, DPP Head of Business Development and Delivery says: "News Exchange will enable the efficient movement of story metadata from the newsroom out to the reporter and cameraman in the field. "They record their video clips, and with that video file it will then send the metadata from the newsroom, now augmented with data from the camera and in an XML file, to be imported back into the newsroom. "This means the metadata with the story will pass with the video throughout the chain. There are immediate benefits to journalists like less tagging," he adds.