The eu-FAIRnews: A Preliminary Exploration of Bridging Disinformation and Digital Justice Through FAIR Data Practices in Online News Sources

Freedom of speech is a crucial right. While the digital realm has allowed for greater expansion of free expression, it has also facilitated anonymous sharing of content. The veracity of news is increasingly threatened by the difficulty of tracking data, sources, and those responsible for data inconsistencies, which contribute to disinformation. Anonymity has become a potential threat, enabling the spread of disinformation without consequences and challenging regulations. The “untraceability” of data modifications, data inconsistencies, and anonymity of authors lead us to consider whether the FAIR (Findable, Accessible, Interoperable, Reusable) principles could be applied to news sources to determine if they can help counter disinformation, while still respecting the right to freedom of speech and enhancing the right to clear information for all and the journalists’ right to professional integrity. The difficulties in regulating disinformation while respecting freedom of speech, combined with the increasing presence of anomalies in data from news sources and the lack of Italian corpora for training detection/prediction models, led us to develop the eu-FAIRnews. Initially conceived as a scraping tool to collect news and data from various sources, eu-FAIRnews is now being implemented to explore the compatibility of news sources and articles with the FAIR principles and their relation to news quality, disinformation, and digital justice. The eu-FAIRnews tool reflects real-world challenges in defending against this type of hybrid threat. Finally, the tool guides users through the visualization of data, results, and preliminary scores, enhancing transparency, accountability, and media awareness.