The healthcare sector is currently undergoing a remarkable transformation due to rapid advancements in digital technology. In particular, the integration of digital tools into public health systems enhances epidemic forecasting and response, aiding policymakers and researchers in making informed decisions swiftly. However, current event-based monitoring tools often struggle to capture the complex dynamics of outbreaks. In response, this ongoing work aims to employ semantic technologies and knowledge graphs to improve the exploration of epidemiological information extracted from curated news and reports. By using knowledge graphs, we aim to offer machine-readable and interpretable information, thereby enhancing the analysis and understanding of epidemic surveillance. This work includes the development of semantic services and interactive visualization dashboards to facilitate the exploration of knowledge graphs, providing insights into the trends and dynamics of event-based epidemic surveillance over time and across regions.
CONSOLI Sergio;
COLETTI Pietro;
MARKOV Peter;
ORFEI Lia;
BIAZZO Indaco;
SCHUH Lea;
STEFANOVITCH Nicolas;
BERTOLINI Lorenzo;
CERESA Mario;
STILIANAKIS Nikolaos;
2026-05-28
SPRINGER VERLAG
JRC142168
1611-3349 (online),
https://link.springer.com/chapter/10.1007/978-3-032-21477-5_23,
https://publications.jrc.ec.europa.eu/repository/handle/JRC142168,
10.1007/978-3-032-21477-5_23 (online),
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